Advanced Markov Chain Monte Carlo Methods by Faming Liang, Ch... - 9780470748268

Advanced Markov Chain Monte Carlo MethodsLearning from Past Samples\nAuthor(s): Faming Liang, Chuanhai Liu, Raymond Carroll\nFormat: Hardback\nPublisher: John Wiley & Sons Inc, United States\nImprint: John Wiley & Sons Inc\nISBN-13: 9780470748268, 978-0470748268\nSynopsis\nMarkov Chain Monte Carlo (MCMC) methods are now an indispensable tool 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. Key Features:\nExpanded coverage of the stochastic approximation Monte Carlo and dynamic weighting algorithms that are essentially immune to local trap problems. A detailed discussion of the Monte Carlo Metropolis-Hastings algorithm that can be used for sampling from distributions with intractable normalizing c.