ERIC Number: EJ1079884
Record Type: Journal
Publication Date: 2015-Oct
Pages: 14
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1076-9986
EISSN: EISSN-1935-1054
Stan: A Probabilistic Programming Language for Bayesian Inference and Optimization
Andrew Gelman; Daniel Lee; Jiqiang Guo
Journal of Educational and Behavioral Statistics, v40 n5 p530-543 Oct 2015
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.
Descriptors: Programming Languages, Bayesian Statistics, Inferences, Monte Carlo Methods, Hierarchical Linear Modeling, Probability, Regression (Statistics), Statistical Distributions, Computer Software
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: Institute of Education Sciences (ED); National Science Foundation (NSF); Office of Naval Research (ONR)
Authoring Institution: N/A
IES Funded: Yes
Grant or Contract Numbers: N/A