A new textbook written by Liang, Liu, and Carroll

08-24-2010

Professor Chuanhai Liu (Department of Statistics, Purdue University) and his colleagues Professors Faming Liang and Raymond J. Carroll (both from the Department of Statistics, Texas A&M University) have authored the text, "Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples". The text is part of the Wiley Series in Computational Statistics.

Markov Chain Monte Carlo (MCMC) methods are now an essential component of the standard set of techniques in scientific computing. This book discusses recent developments of MCMC methods with an emphasis on those making use of past sample information during simulations. The application examples are drawn from diverse fields such as bioinformatics, machine learning, social science, combinatorial optimization, and computational physics. Read more at: http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470748265.html