Some references for Markov chain Monte Carlo methods

Note: comprehensive treatment of Monte Carlo methods (including MCMC, Importance Sampling and recently developed techniques) with plenty of related theoretical details. The level of the text is generally more advanced than the other two references below (notation is sometimes measure-theoretic). The book is an excellent reference with a view towards a lot of the latest research on advanced MCMC techniques.

Note: well written chapters by several different experts on a variety of topics from MCMC basics to specialized applications of MCMC. Useful practical advice for first time MCMC users although the information is somewhat dated.

Note: this book has descriptions about a few advanced MCMC strategies along with a thorough treatment of Importance Sampling and Sequential Importance Sampling. It is hence a bit more specialized than the other two references.

Other references for Monte Carlo and Statistical Computing:

Some references for the idea of using estimated standard errors to stop an MCMC run: Markov chain Monte Carlo: Can we trust the third significant figure? and a more technical reference: Fixed Width Output Analysis for Markov chain Monte Carlo (2006), Journal of the American Statistical Association.