Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Stan: A Probabilistic Programming Language | Carpenter | Journal of Statistical Software
Authors: Bob Carpenter, Andrew Gelman, Matthew D. Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus Brubaker, Jiqiang Guo, Peter Li, Allen Riddell
Title: Stan: A Probabilistic Programming Language
Abstract: Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.

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Paper: Stan: A Probabilistic Programming Language     Download PDF (Downloads: 4050)
Supplements:
cmdstan-2.14.0.tar.gz: Stan source package Download (Downloads: 97; 29MB)
pystan-2.14.0.0.tar.gz: Python source package Download (Downloads: 85; 373KB)
rstan-2.14.1.tar.gz: R source package Download (Downloads: 135; 2MB)
v76i01-replication.zip: Replication code for the examples Download (Downloads: 141; 2KB)

DOI: 10.18637/jss.v076.i01

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