stan-dev/pystan: v2.17.1.0 with CVODES support

Description

PyStan provides a Python interface to Stan, a package for Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo. Stan® is a state-of-the-art platform for statistical modeling and high-performance statistical computation. Thousands of users rely on Stan for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business. Users specify log density functions in Stan’s probabilistic programming language and get: full Bayesian statistical inference with MCMC sampling (NUTS, HMC) approximate Bayesian inference with variational inference (ADVI) penalized maximum likelihood estimation with optimization (L-BFGS) The title and description of this software correspond with the situation when the software metadata was imported to ACRIS. The most recent version of metadata is available in the original repository.
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Year of publication

2018

Type of data

Authors

Department of Civil Engineering

Ari Hartikainen - Creator

Aaron Darling - Contributor

Alexander Rudiuk - Contributor

Allen Riddell - Contributor

Daniel Chen - Contributor

Daniel Lee - Contributor

Dougal J. Sutherland - Contributor

Joerg Rings - Contributor

Kenneth C. Arnold - Contributor

Kyle Foreman - Contributor

Marco Inacio - Contributor

Max Shron - Contributor

Richard C. Gerkin - Contributor

Shinya Suzuki - Contributor

Skipper Seabold - Contributor

Stephan Hoyer - Contributor

Stephen Hoover - Contributor

Takahiro Kubo - Contributor

Tobias Erhardt - Contributor

Todd Small - Contributor

Zenodo - Publisher

Project

Other information

Fields of science

Computer and information sciences

Language

Open access

Open

License

Other

Keywords

Subject headings

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