Bridging the gap between new research and application, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference provides a concise, up-to-date, and integrated account of recent developments in Markov chain Monte Carlo (MCMC) for performing Bayesian inference. This volume, which was developed from a short course taught by the author at a meeting of Brazilian statisticians and probabilists, retains the didactic character of the original course text. The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians