Bayes Home
Jaynes Errata

Free Software for Bayesian Statistical Inference

Regression and classification:

General statistical analysis:

  • BUGS / WinBUGS (Bayesian Inference Using Gibbs Sampling). Probably the most popular and flexible software for Bayesian statistics around. Has a powerful model description language, and uses Markov Chain Monte Carlo to do a full Bayesian analysis.
  • BayesX. Software for semiparametric regression using MCMC, inference for STAR (structured additive predictor) models, model selection for Gaussian and non-Gaussian DAGs, etc.
  • R. An open-source implementation of the S language for data analysis. Mostly oriented towards frequentist statistics, but there are some packages for Bayesian statistics.
  • bugs.R: Functions for running WinBUGS from R.
  • Bayesian Output Analysis Program. Convergence diagnostics for Markov Chain Monte Carlo.
  • R-CODA. Convergence diagnostics for Markov Chain Monte Carlo.
  • Software for Bayesian meta-analysis: hblm in S-plus. Hierarchical Bayes Linear Models. Used to combine the results from several independent studies. S-plus code and documentation.
  • BACC: Bayesian Analysis, Computation, and Communication. A collection of statistical routines implemented for R, S-plus, and Matlab.
  • Software and Datasets (Adrian Raftery). A collection of S functions for various statical analyses, many of them Bayesian or useful as part of a full Bayesian analysis.
  • Bayesian Model Selection Software (Adrian Raftery). S functions for computing posterior probabilities of models.
  • Bayesian Model Averaging Home Page. Software in S for model averageing, which accounts for uncerty in model selection when making predictions.

Bayesian networks:

Time Series / dynamic models:


  • First Bayes. Teaching package for elementary Bayesian statistics. Runs on all versions of Windows.
  • Autoclass: automatic class discovery. Discovers clusters/classes in data that may include both real and discrete attributes. Alternate link.
  • Autoclass C. C language implementation of Autoclass.
  • Model-based Clustering Software (MCLUST / EMCLUST). Written in FORTRAN and interfaced to S-plus and R.
  • GSL: Gnu Scientific Library. Contains many functions that are useful for writing statistical software.
  • MCSim. Software that takes a model specification and creates a C program to do Markov Chain Monte Carlo evaluation of that model. The advantage is speed of simulation.
  • Hydra MCMC Library. A platform-neutral library for performing Markov chain Monte Carlo, written in Java. Alternate links: Sourceforge, download page.
  • BAYESPACK (scroll down to BAYESPACK entry in list after clicking on link). A collection of Fortran software for numerical evaluation of integrals that arise in Bayesian statistical analysis. Paper describing the system.
  • BayeSys. Software for Markov Chain Monte Carlo and computation on evidence (a.k.a. model likelihood or marginal likelihood).
  • OpenNLP Maxent. Java package for training and using maximum-entropy models.
  • [B/D]: The Bayes Linear Programming Language.