R package for Inference of differentially methylated regions (DMRs) from bisulfite sequencing

Gaussian dynamic Bayesian networks structure learning and inference based on the bnlearn package

Bayesian Regression with INLA

Data Science courses in R from HarvardX

Parametric and non-parametric statistical tests

A Unified Framework for Random Forest Prediction Error Estimation

Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood

Robust Econometric Inference for Predictive Regressions

R-package for relational event models (one- and two-mode networks)

Inference in Bayesian Networks with R

Framework for estimating parameters and the empirical sandwich covariance matrix from a set of unbiased estimating equations (i.e. M-estimation) in R.

Infers species direct association networks

Threshold Selection and Uncertainty for Extreme Value Analysis

R-package ffscb: fast n' fair simultaneous confidence bands for functional parameters. The statistical theory and methodology is described in our paper https://arxiv.org/abs/1910.00131. A description of the functions in our R-package can be found at www.dliebl.com/ffscb/.

Statistical inference of genetic functions in phylogenetic trees

Accurate and robust inference of genetic ancestry from cancer-derived molecular data across genomic platforms

Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis

R package with a set of functions to select the optimal block-length for a dependent bootstrap (block-bootstrap). Includes the Hall, Horowitz, and Jing (1995) cross-validation method and the Politis and White (2004) Spectral Density Plug-in method.

Gaussian Mixture Graphical Model Learning and Inference