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Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples - Wiley Series in Computational Statistics Liang, Faming (Texas A&M University, USA)
Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples - Wiley Series in Computational Statistics
Liang, Faming (Texas A&M University, USA)
* Presents the latest developments in Monte Carlo research. * Provides a toolkit for simulating complex systems using MCMC. * Introduces a wide range of algorithms including Gibbs sampler, Metropolis-Hastings and an overview of sequential Monte Carlo algorithms.
378 pages, Illustrations
| Media | Books Hardcover Book (Book with hard spine and cover) |
| Released | August 23, 2010 |
| ISBN13 | 9780470748268 |
| Publishers | John Wiley & Sons Inc |
| Pages | 384 |
| Dimensions | 233 × 159 × 26 mm · 680 g |
| Language | English |