Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition

By Dani Gamerman, Hedibert Freitas Lopes, Hedibert F. Lopes, et al.

Book Overview

Incorporating changes in theory and highlighting new applications, this book presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. This second edition includes many new examples in the chapters on Gibbs sampling and Metropolis-Hastings algorithms. It incorporates all the recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection. It also features many worked examples and discusses computation using both R and WinBUGS. With additional exercises and selected solutions within the text, it offers all data sets and software for download from the Web.

• Format: Hardcover
• Language: English
• ISBN: 1584885874
• ISBN13: 9781584885870
• Release Date: May 2006
• Publisher: CRC Press
• Length: 342 Pages
• Weight: 1.60 lbs.
• Dimensions: 0.9" x 6.1" x 9.5"