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Free software portal; Mathematics portal; Bambi is a high-level Bayesian model-building interface written in Python.It works with the PyMC probabilistic programming framework. . Bambi provides an interface to build and solve Bayesian generalized (non-)linear multivariate multilevel mode
OpenBUGS is a software application for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. OpenBUGS is the open source variant of WinBUGS (Bayesian inference Using Gibbs Sampling). It runs under Microsoft Windows and Linux, as well as from inside the R statistical package.
Stan: A probabilistic programming language for Bayesian inference and optimization, Journal of Educational and Behavioral Statistics. Hoffman, Matthew D., Bob Carpenter, and Andrew Gelman (2012). Stan, scalable software for Bayesian modeling Archived 2015-01-21 at the Wayback Machine, Proceedings of the NIPS Workshop on Probabilistic Programming.
Bayesian: Bayesian: Acceptance Sampling X (repeated) (M)AN(C)OVA and non-parametrics ( ) ( ) Audit - Statistical Methods for Auditing X X Bain - Bayesian informative hypotheses evaluation X BSTS - Bayesian structural time series X Circular / Directional Statistics - analysis of directions, often angles X X X Cochrane Meta-Analyses X X
PyMC Development Team: ... It is a rewrite from scratch of the previous version of the PyMC software. [7] ... Bambi is a high-level Bayesian model-building interface ...
Free and open-source software portal; Pages in category "Free Bayesian statistics software" The following 9 pages are in this category, out of 9 total.
Bayesian inference using Gibbs sampling (BUGS) is a statistical software for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods. It was developed by David Spiegelhalter at the Medical Research Council Biostatistics Unit in Cambridge in 1989 and released as free software in 1991.
Just another Gibbs sampler (JAGS) is a program for simulation from Bayesian hierarchical models using Markov chain Monte Carlo (MCMC), developed by Martyn Plummer. JAGS has been employed for statistical work in many fields, for example ecology, management, and genetics. [2] [3] [4]
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