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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Veröffentlicht in:Journal of educational and behavioral statistics Jg. 40; H. 5; S. 530 - 543
Hauptverfasser: Gelman, Andrew, Lee, Daniel, Guo, Jiqiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Los Angeles, CA SAGE Publications 01.10.2015
American Educational Research Association
Schlagworte:
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-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:1076-9986
1935-1054
DOI:10.3102/1076998615606113