Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference (Chapman & Hall/CRC Texts in Statistical Science) - Tapa dura

..."a must for every research library, and should be given serious consideration for use as a graduate text" -Short Book Reviews of the ISI "nicely focused, elementary-level coveragemakes this book a suitable choice for an introductory course." -Journal of the ASA, March, 2000

Bridging the gap between research and application, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference provides a concise, and integrated account of 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. It describes each component of the theory in detail and outlines related software, which is of particular benefit to applied scientists.