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

Beskrivning

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)
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Publiceringsår

2018

Typ av data

Upphovspersoner

Department of Civil Engineering

Aaron Darling - Upphovsperson

Alexander Rudiuk - Upphovsperson

Allen Riddell - Upphovsperson

Ari Hartikainen - Upphovsperson

Daniel Chen - Upphovsperson

Daniel Lee - Upphovsperson

Dougal J. Sutherland - Upphovsperson

Joerg Rings - Upphovsperson

Kenneth C. Arnold - Upphovsperson

Kyle Foreman - Upphovsperson

Marco Inacio - Upphovsperson

Max Shron - Upphovsperson

Richard C. Gerkin - Upphovsperson

Shinya Suzuki - Upphovsperson

Skipper Seabold - Upphovsperson

Stephan Hoyer - Upphovsperson

Stephen Hoover - Upphovsperson

Takahiro Kubo - Upphovsperson

Tobias Erhardt - Upphovsperson

Todd Small - Upphovsperson

Zenodo - Utgivare

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Data- och informationsvetenskap

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