Stan: A Probabilistic Programming Language for Bayesian Inference and Optimization

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...

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Bibliographic Details
Published in:Journal of educational and behavioral statistics Vol. 40; no. 5; pp. 530 - 543
Main Authors: Gelman, Andrew, Lee, Daniel, Guo, Jiqiang
Format: Journal Article
Language:English
Published: Los Angeles, CA SAGE Publications 01.10.2015
American Educational Research Association
Subjects:
Bayesian analysis
Bayesian Statistics
Computer Software
Hierarchical Linear Modeling
Inferences
Mathematical models
Monte Carlo Methods
Open source software
Optimization techniques
Probability
Programming Languages
Regression (Statistics)
Regression analysis
Software Review
Statistical Distributions
Statistical inference
hierarchical models
statistical computing
Bayesian inference
probabilistic programming
ISSN:1076-9986, 1935-1054
Online Access:Get full text
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Summary: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.
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ISSN:1076-9986
1935-1054
DOI:10.3102/1076998615606113