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Advanced Markov Chain Monte Carlo
Hardcover
Series: Wiley Computational Statistics
ISBN13: 9780470748268
Publisher: John Wiley & Sons
Published: Aug 10 2010
Pages: 384
Weight: 1.50
Height: 1.00 Width: 6.20 Depth: 9.10
Language: English
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 Monte Carlo Metropolis-Hastings algorithm that can be used for sampling from distributions with intractable normalizing constants.
- Up-to-date accounts of recent developments of the Gibbs sampler.
- Comprehensive overviews of the population-based MCMC algorithms and the MCMC algorithms with adaptive proposals.
This book can be used as a textbook or a reference book for a one-semester graduate course in statistics, computational biology, engineering, and computer sciences. Applied or theoretical researchers will also find this book beneficial.
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