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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.
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
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.
JASP – A free software alternative to IBM SPSS Statistics with additional option for Bayesian methods; JMulTi – For econometric analysis, specialised in univariate and multivariate time series analysis; Just another Gibbs sampler (JAGS) – a program for analyzing Bayesian hierarchical models using Markov chain Monte Carlo developed by ...
WinBUGS is statistical software for Bayesian analysis using Markov chain Monte Carlo (MCMC) methods. It is based on the BUGS (Bayesian inference Using Gibbs Sampling) project started in 1989. It runs under Microsoft Windows, though it can also be run on Linux or Mac using Wine. [1]
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.
Infer.NET is a free and open source.NET software library for machine learning. [2] It supports running Bayesian inference in graphical models and can also be used for probabilistic programming . [ 3 ]
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
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