Statistics

AStA Advances in Statistical Analysis is a quarterly journal that publishes original contributions on statistical methodology, applications, and review articles.

• Official journal of the German Statistical Society.
• Examines exciting new methodological developments in traditional areas of research.
• Contributions at the interface with data science, statistical learning, and machine learning are welcome.
• Encourages submissions from diverse application areas including social sciences, business, economics, engineering, environmental sciences, and life sciences.  
• Comprised of three designated sections: Statistical Applications, Statistical Methodology, and Statistical Reviews.

Das Wirtschafts- und Sozialstatistische Archiv ist eine Zeitschrift der Deutschen Statistischen Gesellschaft. Sie versteht sich als zentrales deutschsprachiges Organ für die Publikation wirtschafts- und sozialstatistischer Arbeiten. Diese behandeln substantielle Fragestellungen der Wirtschafts- und Sozialwissenschaften mit einer Methodik, die Konzepte der klassischen Wirtschaftsstatistik mit modernen mathematisch geprägten statistischen Ansätzen verbindet. Publiziert werden methodisch fundierte, problemorientierte Arbeiten. Im Vordergrund stehen Themen, die für eine breitere wissenschaftliche und auch außerwissenschaftliche Öffentlichkeit von Interesse sind.

The international journal Advances in Data Analysis and Classification (ADAC) is designed as a forum for high standard publications on research and applications concerning the extraction of knowable aspects from many types of data. It publishes articles on such topics as structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; methods for the extraction of knowledge from data, and applications of advanced methods in specific domains of practice. Articles illustrate how new domain-specific knowledge can be made available from data by skillful use of data analysis methods. The journal also publishes survey papers that outline, and illuminate the basic ideas and techniques of special approaches.

Supported by the International Federation of Classification Societies, and funded by the Italian, German, and Japanese Classification Societies (CLADAG, GfKl, JCS).
Officially cited as: Adv Data Anal Classif

Annals of the Institute of Statistical Mathematics (AISM) aims to provide a forum for open communication among statisticians, and to contribute to the advancement of statistics as a science to enable humans to handle information in order to cope with uncertainties. It publishes high-quality papers that shed new light on the theoretical, computational and/or methodological aspects of statistical science. Emphasis is placed on (a) development of new methodologies motivated by real data, (b) development of unifying theories, and (c) analysis and improvement of existing methodologies and theories. It also seeks to contribute to statistical science in machine learning and econometrics. AISM is trying to make faster decisions after the reception. For example, around 60%, 80%, and 90% of submissions received from July 2019 to June 2020 had a review time from receipt to first decision of 1, 3, and 5 months or less, respectively.

Behaviormetrika is a fully refereed international journal focused on new theoretical and empirical quantitative approaches in data science.

• The oldest journal addressing the topic of data science, launched in 1974.
• Publishes original research papers, notes, and review articles in various methodologies and fields.
• Advocates data science as an interdisciplinary field, using statistical methods to extract meaningful knowledge from all forms of data.
• Aims to reveal the features or hidden structure of complicated natural, human, and social phenomena through data.

Computational Statistics is an international journal fostering applications and methodological research in computational statistics and data science.

• Emphasizes the contribution to and influence of computing on statistics and vice versa.
• Provides a forum for computer scientists, applied mathematicians, and statisticians.
• Publishes package reports and software articles on various Statistics and Data Science areas.

Extremes is a dedicated platform for the publication of original research in statistical extreme value theory and its applications across various fields.

• Advances research by providing a unified forum for top-tier papers in the field.
• Presents authoritative reviews and case studies of theoretical advances and extreme value methods.
• Broad application across science, engineering, economics, and other fields.

- Digital cultural heritage with a special focus on born digital documents / archives
- Data visualization, information retrieval, statistical analysis, big data
- Natural language processing, named entity recognition, topic modelling, text mining
- Digital scholarly editing
- Semantic web technology, network theory
- 3D modelling, digital visualization
- Teaching Digital Humanities

Japanese Journal of Statistics and Data Science is an international forum publishing original articles in statistical theories and diverse fields related to data science.

• Provides coverage spanning all aspects of the discipline of statistics.
• Successor of the Journal of the Japan Statistical Society and the Journal of the Japanese Society of Computational Statistics.
• An official journal of the Japanese Federation of Statistical Science Associations.
• Combines traditional statistical science and relatively new data science.
• Promotes and extends the use of statistics in science.

The Journal of Agricultural, Biological and Environmental Statistics (JABES) is dedicated to introducing new statistical methods to solve practical problems in the agricultural, biological, and environmental sciences.

• A joint publication of the International Biometric Society and the American Statistical Association.
• Contributes to the development and use of statistical methods in the agricultural, biological, and environmental sciences.
• Encourages the submission of interdisciplinary papers and those applying existing methods in novel contexts.
• Publishes expository, review, and survey articles addressing broad-based statistical issues.
• Requires real data for illustration of statistical methods, along with the provision of computer code as supplementary material.

Journal of Classification presents original work in the field of classification across multiple disciplines.

• Covers classification, broadly defined, including supervised classification, unsupervised classification (clustering), semi-supervised classification, statistical computing, numerical taxonomy, multivariate statistics, and machine learning.
• Publishes work from a wide range of disciplines including statistics, computer science, psychometrics, biometrics, econometrics, engineering, mathematics, and more.
• Publishes three times a year, comprising articles, short notes, comments, software abstracts, and book reviews.

The Journal of Statistical Theory and Applications is dedicated to the publication of original research papers in the area of statistical sciences and related applications. The aim of the journal is to publish theoretical articles as well as articles about applications in the field, reviews and short communications. The journal has a distinguished Editorial Board consisting of Editors with outstanding academic qualifications. All papers submitted for publication are subject to a strict peer review process and Authors are requested to suggest several names of potential referees with the submission of their manuscript. Note that the Editors retain the sole right to decide whether the suggested reviewers will be used or not and that the final acceptance decision of any paper is made by the Editor-in-Chief.

Journal of Statistical Theory and Practice is a broad-based journal that publishes original research and reviews in statistical sciences.

• Submission of original research papers, significant review articles, and book reviews are encouraged.
• Publishes editorials on 'Life and Works' of eminent scholars.
• Regularly publishes special issues on targeted topics.
• Covers all traditional topics in statistical theory and applications.
• Also publishes articles in the field of data sciences including machine learning.

Journal of the Indian Society for Probability and Statistics is a scholarly publication fostering knowledge in statistics, probability, and operations research along with their applications in in agricultural, biological, economics, health, physical and social sciences.

• Publishes original research and review articles in all branches of probability and statistics.
• Aims to bridge the gap between academicians and practitioners.
• An official publication of the Indian Society for Probability and Statistics.
• Welcomes articles on innovative case studies, teaching methodologies and review articles on current topics.
• Maintains rigor through strict review processes and high-quality global reviewers.

Journal of the Korean Statistical Society is dedicated to publishing original contributions to the theory and methodology of statistics and probability.

• Welcomes papers with an overview of current statistical research and innovative applications of statistical methodology.
• Encourages contributions that identify promising directions for future work.
• Official journal of Korean Statistical Society established in 1973

Lifetime Data Analysis is the only journal dedicated to statistical methods and applications for lifetime data.

• Advances statistical science in various applied fields dealing with lifetime data.
• Coverage includes actuarial science, economics, engineering, environmental sciences, management, medicine, operations research, public health, and social and behavioral sciences.
• Promotes a broad range of topics including accelerated failure time models, degradation processes, meta-analysis, and reliability methods.
• Highlights applications of time-to-event data.

Founded in 1920 by Corrado Gini, METRON presents original articles on statistical methodology and statisticsl applications, as well as discussions of results achieved by statistical methods in different branches of science.

• Publishes original papers that contribute significant advances to general statistical methodology, as well as advances motivated by specific applications.
• Open to all methodologies, emphasizing quality research that approaches statistical topics with originality and clarity.
• Associated with the Dipartimento di Scienze Statistiche, Sapienza Università di Roma.

Past editors
Corrado Gini (1920-1964)
Vittorio Castellano (1965-1980)
Carlo Benedetti (1981-1990)
Mario Badaloni (1991-2002)
Giovanni Maria Giorgi (2003-2006, 2013-2017)
Pier Luigi Conti (2007-2012)
Marco Alfo (2018-2024)

"Mathematical Methods of Statistics is an international journal focusing on the mathematical foundations of statistical theory.

• Primarily publishes research papers with complete proofs and occasionally review papers on statistical problems.
• Publishes applications of statistics that contain new theoretical developments to the underlying methods.
• Provides an outlet for research in advanced statistical methodology.
• Covers all areas of mathematical statistics including asymptotic theory, sequential analysis, optimal stopping times, and regression analysis."

Methodology and Computing in Applied Probability is a journal that publishes high quality research and review articles in areas of applied probability that emphasize methodology and computing.

• Highlights articles examining important applications and detailed case studies.
• Covers a broad range of interests including algorithms, finance, mathematical physics, and more.
• Uses Springer Nature’s Article Processing Platform, Snapp, for peer reviews.
• A favorable choice for authors, with 100% surveyed reporting likelihood to publish again in the journal.

Metrika is an international journal that focuses on the exploration of mathematical statistics and statistical methods.

• Publishes original research papers in the field of theoretical and applied statistics.
• Emphasizes new developments in theoretical statistics and statistical modeling.
• Addresses the innovative applicability of proposed statistical methods and results.
• Highly rated by authors for the probability of future publication.