JSS logo Established in 1996, the Journal of Statistical Software publishes articles on statistical software along with the source code of the software itself and replication code for all empirical results. Furthermore, shorter code snippets are published as well as book reviews and software reviews. All contents are freely available online under open licenses. We aim to present research that demonstrates the joint evolution of computational and statistical methods and facilitates their application in practice. Implementations can use languages and environments like R, Python, Julia, MATLAB, SAS, Stata, C, C++, Fortran, among others. See our mission statement for more details.

Blang: Bayesian Declarative Modeling of General Data Structures and Inference via Algorithms Based on Distribution Continua

Alexandre Bouchard-Côté, Kevin Chern, Davor Cubranic, Sahand Hosseini, Justin Hume, Matteo Lepur, Zihui Ouyang, Giorgio Sgarbi
Vol. 103, Issue 11

Robust Mediation Analysis: The R Package robmed

Andreas Alfons, Nüfer Y. Ateş, Patrick J. F. Groenen
Vol. 103, Issue 13

Bambi: A Simple Interface for Fitting Bayesian Linear Models in Python

Tomás Capretto, Camen Piho, Ravin Kumar, Jacob Westfall, Tal Yarkoni, Osvaldo A Martin
Vol. 103, Issue 15

Learning Base R (2nd Edition)

James E. Helmreich
Vol. 103, Book Review 1

Python and R for the Modern Data Scientist

Christopher J. Lortie
Vol. 103, Book Review 2
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