Stan: A Probabilistic Programming Language for Bayesian Inference and Optimization

被引：361
|
作者：
Gelman, Andrew [1 ]
Lee, Daniel [2 ]
Guo, Jiqiang [2 ]
机构：
[1] Columbia Univ, Stat & Polit Sci, New York, NY 10027 USA
[2] Columbia Univ, New York, NY 10027 USA
来源：
JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS | 2015年 / 40卷 / 05期
基金：
美国国家科学基金会;
关键词：
Bayesian inference; hierarchical models; probabilistic programming; statistical computing;
D O I：
10.3102/1076998615606113
中图分类号：
G40 [教育学];
学科分类号：
040101 ; 120403 ;
摘要：
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.
引用
收藏
页码：530 / 543
页数：14
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