This is a reference not a textbook, but there is enough introductory matter that graduate students and researchers new to Markov Chain Monte Carlo (MCMC) statistical methods can become acquainted with the basic theory, algorithms, and applications. The first half looks at the foundations, methodology, and algorithms; the second half samples practical applications in a number of fields. Among the topics are reversible jump MCMC, MCMC using Hamiltonian dynamics, estimating with confidence, spatial point processes, an MCMC-based analysis of a multilevel model for functional magnetic resonance imaging data, statistical ecology, educational research, fisheries science, and analyzing rural-urban migration in Thailand. Annotation ©2011 Book News, Inc., Portland, OR (booknews.com)