Advanced Markov Chain Monte Carlo Methods
Product details
- ISBN 9780470748268
- Weight: 737g
- Dimensions: 163 x 233mm
- Publication Date: 16 Jul 2010
- Publisher: John Wiley & Sons Inc
- Publication City/Country: US
- Product Form: Hardback
- Language: English
Our Delivery Time Frames Explained
2-4 Working Days: Available in-stock
10-20 Working Days: On Backorder
Will Deliver When Available: On Pre-Order or Reprinting
We ship your order once all items have arrived at our warehouse and are processed. Need those 2-4 day shipping items sooner? Just place a separate order for them!
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.
Faming Liang, Associate Professor, Department of Statistics, Texas A&M University.
Chuanhai Liu, Professor, Department of Statistics, Purdue University.
Raymond J. Carroll, Distinguished Professor, Department of Statistics, Texas A&M University.