Recent Publications
Articles
| dbscan: Fast Density-Based Clustering with R | |
| Michael Hahsler, Matthew Piekenbrock, Derek Doran |
| stm: An R Package for Structural Topic Models | |
| Margaret E. Roberts, Brandon M. Stewart, Dustin Tingley |
| sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo | |
| Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth |
| Markov-Switching GARCH Models in R: The MSGARCH Package | |
| David Ardia, Keven Bluteau, Kris Boudt, Leopoldo Catania, Denis-Alexandre Trottier |
| Depth and Depth-Based Classification with R Package ddalpha | |
| Oleksii Pokotylo, Pavlo Mozharovskyi, Rainer Dyckerhoff |
| Psychological Test Toolbox: A New Tool to Compute Factor Analysis Controlling Response Bias | |
| David Navarro-Gonzalez, Andreu Vigil-Colet, Pere Joan Ferrando, Urbano Lorenzo-Seva |
| The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators | |
| Ann-Kristin Kreutzmann, Sören Pannier, Natalia Rojas-Perilla, Timo Schmid, Matthias Templ, Nikos Tzavidis |
| nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference | |
| Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell |
| Fuzzy Forests: Extending Random Forest Feature Selection for Correlated, High-Dimensional Data | |
| Daniel Conn, Tuck Ngun, Gang Li, Christina M. Ramirez |
| Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R | |
| Angelos Markos, Alfonso Iodice D'Enza, Michel van de Velden |
| Learning Large-Scale Bayesian Networks with the sparsebn Package | |
| Bryon Aragam, Jiaying Gu, Qing Zhou |
| SimInf: An R Package for Data-Driven Stochastic Disease Spread Simulations | |
| Stefan Widgren, Pavol Bauer, Robin Eriksson, Stefan Engblom |
Established in 1996, the Journal of Statistical Software publishes articles, book reviews, code snippets, and software reviews on the subject of statistical software and algorithms. The contents are freely available on-line. For both articles and code snippets the source code is published along with the paper. Statistical software is the key link between statistical methods and their application in practice. Software that makes this link is the province of the journal, and may be realized as, for instance, tools for large scale computing, database technology, desktop computing, distributed systems, the World Wide Web, reproducible research, archiving and documentation, and embedded systems. We attempt to present research that demonstrates the joint evolution of computational and statistical methods and techniques. Implementations can use languages such as C, C++, S, Fortran, Java, PHP, Python and Ruby or environments such as Mathematica, MATLAB, R, S-PLUS, SAS, Stata, and XLISP-STAT.
Announcements
| Changes in editorial team | |
| In response to the continuing success of JSS we have expanded our editorial team aiming to further enhance the quality of publications and lower reviewing times and publication delays. First, Torsten Hothorn has joined as the fourth editor-in-chief. Second, we now have four editorial assistants who help with managing submissions, work flows, editing, technical checks, web services, etc.: Aaron Danielson, Gregor Kastner, Heidi Seibold, Reto Stauffer. Welcome to all the new members of the editorial team! |
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| JSS Celebrates 20 Years: Special Volume 73 | |
| 2016 marks the 20th anniversary of the Journal of Statistical Software. We celebrate the anniversary with a Festschrift for Jan de Leeuw, the journal's founding editor, which is now online as Special Volume 73 (Editors: Patrick Mair, Katharine Mullen). |
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| New JSS server | |
| The Journal of Statistical Software moved to a new server based on Open Journal Systems (OJS, http://pkp.sfu.ca/ojs/) which not only hosts published software/manuscripts but also provides a full editorial system. Thus, all submissions, reviews, etc. can now be made through the new OJS system. |
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| More Announcements... |
Support
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As a matter of principle, JSS charges no author fees or subscription fees. Our editors, reviewers, and programmers are volunteers. UCLA Statistics and Universität Innsbruck contribute support staff, website maintenance, website hosting, and some graduate student support. Because of our success and growth we do need more resources in the future. You can support us by becoming a member of the Foundation for Open Access Statistics at www.foastat.org, and by contributing on their donation page. |