Presenting a comprehensive introduction to the methods of this valuable simulation technique, this second edition includes new chapters on Gibbs sampling and Metropolis-Hastings algorithms. It incorporates all the recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, and more. With additional exercises and selected solutions within the text, it offers all data sets and software for download from the Web.

Dani Gamerman, Hedibert F. Lopes

Introduction. Bayesian Inference. Approximate Methods of Inference. Markov Chains. MCMC. Gibbs Sampling. Metropolis-Hastings Algorithms. Further Topics in MCMC.