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MCMC-Related Links

This page contains lists to MCMC-related sites including those holding software, codes and applets that may be useful or of interest to people working in the MCMC area.

General Sites

• McDiag Home Page This is an extremely useful site providing all sorts of useful information about recent and current research on MCMC Convergence Diagnosis.

• Perfect Simulation Home Page This is another useful site, keeping track of current and recent research on perfect simulation.

• Sequential Monte Carlo Methods. This site provides material on sequential Monte Carlo methods focussing attention on particle filtering. There is also a US Mirror of the site.

Books

• Data and Errata for the book "Monte Carlo Methods in Bayesian Computation" by Ming-Hui Chen, Qi-Man Shao, and Joseph G. Ibrahim (Springer, 2000) are available at http://www.stat.uconn.edu/~mhchen/mcbook.
• Data and BUGS code for the book "Bayesian Survival Analysis" by J. Ibrahim, M-H Chen and D. Sinha (Springer, 2001) are available at http://www.stat.uconn.edu/~mhchen/survbook.

MCMC Software

• The Bugs Software Package. This is a powerful statistical package for performing MCMC simulations. There is also a US mirror.

• HYDRA MCMC Library. HYDRA is an open-source, platform-neutral library for performing Markov Chain Monte Carlo. It implements the logic of standard MCMC samplers within a framework designed to be easy to use and to extend while allowing integration with other software tools. It provides methods for implementing MCMC samplers using Metropolis, Metropolis-Hastings, Gibbs methods as well as classes implementing several unique adaptive and multiple chain/parallel MCMC methods.

• Bayesian Output Analysis Program (BOA) An excellent S-PLUS/R program for carrying out convergence diagnostics and statistical and graphical analysis of Monte Carlo sampling output. It can be used as an output processor for the BUGS software or for any other program which produces sampling output.

• Jeff Rosenthal's Java Applets. This a page containing all sorts of Java applets including some illustrative MCMC samplers, such as the independence sampler with exponential target distribution, the Metropolis sampler with exponential target distribution and uniform proposal distributions, and the slice sampler. The latest addition to this set of applets is one to simulate a Coupling from the Past algorithm.

• Dead leaves simulation. This is a very pretty simulation which discusses the ideas of forward and backward simulation and provides a practical illustration of a perfect simulation.

• C-Library for Gaussian Random Fields. Provides a C-library for fast and exact sampling of Gaussian Markov random fields (works for both lattices and graphs) and is intended for block-sampling in MCMC.

• Flexible Bayesian Modeling and MCMC Software. Lets you try out a variety of Markov chain methods on distributions specified by simple formulas (including a BUGS-like notation), and also on more complex models based on neural networks, Gaussian processes, and mixtures.

• Laird's Applet Page. This page provides links to a variety of java applets illustrating different MCMC algorithms.