MCMC Methods for MLP-network and Gaussian Process and Stuff – A documentation for Matlab Toolbox

MCMCstuff toolbox is a collection of Matlab functions for Bayesian inference with Markov chain Monte Carlo (MCMC) methods. This documentation introduces some of the features available in the toolbox. Introduction includes demonstrations of using Bayesian Multilayer Perceptron (MLP) network and Gaussian process in simple regression and classification problems with a hierarchical automatic relevance determination (ARD) prior for covariate related parameters. The regression problems demonstrate the use of Gaussian and Student’s t-distribution residual models and classification is demonstrated for two and three class classification problems. The use of Reversible jump Markov chain Monte Carlo (RJMCMC) method and ARD prior are demonstrated for input variable selection.