Recent Publications
Articles
| Monitoring Data in R with the lumberjack Package | |
| Mark P. J. van der Loo |
| Bayesian Multivariate Spatial Models for Lattice Data with INLA | |
| Francisco Palmí-Perales, Virgilio Gómez-Rubio, Miguel A. Martinez-Beneito |
| Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package | |
| Cristina Tortora, Ryan P. Browne, Aisha ElSherbiny, Brian C. Franczak, Paul D. McNicholas |
| FRK: An R Package for Spatial and Spatio-Temporal Prediction with Large Datasets | |
| Andrew Zammit-Mangion, Noel Cressie |
| Subgroup Identification Using the personalized Package | |
| Jared D. Huling, Menggang Yu |
| NScluster: An R Package for Maximum Palm Likelihood Estimation for Cluster Point Process Models Using OpenMP | |
| Ushio Tanaka, Masami Saga, Junji Nakano |
| Conformal Prediction with Orange | |
| Tomaž Hočevar, Blaž Zupan, Jonna Stålring |
| Analysis of Multiplex Social Networks with R | |
| Matteo Magnani, Luca Rossi, Davide Vega |
Book Reviews
| Data Visualization: Charts, Maps, and Interactive Graphics | |
| Ulrike Grömping |
Software Reviews
| Data Science in Stata 16: Frames, Lasso, and Python Integration | |
| Anson T. Y. Ho, Kim P. Huynh, David T. Jacho-Chávez, Diego Rojas-Baez |
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
| New editorial team members | |
| To sustain the success of JSS in the next years, we have expanded and restructured the editorial team: Rebecca Killick has joined as the fifth Editor-in-Chief, Heidi Seibold became the dedicated Replication Editor for the journal and Reto Stauffer the dedicated Technical Editor. Furthermore, the new Assistant Editors Luisa Barbanti, Balint Tamasi, and Sandra Siegfried support the editing of manuscripts and replication materials. | |
| More Announcements... |
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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. |