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)
Visa merPubliceringsår
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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Vetenskapsområden
Data- och informationsvetenskap
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