Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples

By Unknown Author.

Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples

Description

Markov 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: Expanded coverage of the stochastic approximation Monte Carlo and dynamic weighting algorithms that are essentially immune to local trap problems. A detailed discussion of the Mon...

ISBN(s)

0470748265, 9780470748268

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