Stan: A Probabilistic Programming Language for Bayesian Inference and Optimization. (October 2015)

• Record Type: Journal Article
• Authors: Gelman, Andrew; Lee, Daniel; Guo, Jiqiang
• Is Part Of: Journal of educational and behavioral statistics. Volume 40:Number 5(2015)
• Page Start: 530
• Page End: 543
• Publication Date: 2015-10
• Subjects: Bayesian inference -- hierarchical models -- probabilistic programming -- statistical computing; Educational statistics -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 370.2
• DOI: 10.3102/1076998615606113
• Languages: English
• ISSNs: 1076-9986

Abstract

Stan is a free and open-source C++ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia and has great promise for fitting large and complex statistical models in many areas of application. We discuss Stan from users' and developers' perspectives and illustrate with a simple but nontrivial nonlinear regression example.