Stan

Andrew Gelman, Daniel Lee and Jiqiang Guo
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Andrew Gelman: Columbia University
Daniel Lee: Columbia University
Jiqiang Guo: Columbia University

Journal of Educational and Behavioral Statistics, 2015, vol. 40, issue 5, 530-543

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.

Keywords: Bayesian inference; hierarchical models; probabilistic programming; statistical computing (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:40:y:2015:i:5:p:530-543

DOI: 10.3102/1076998615606113

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