Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples - Wiley Series in Computational Statistics - Liang, Faming (Texas A&M University, USA) - Books - John Wiley & Sons Inc - 9780470748268 - July 16, 2010
In case cover and title do not match, the title is correct

Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples - Wiley Series in Computational Statistics

Liang, Faming (Texas A&M University, USA)

Price
A$ 221.49
excl. VAT

Ordered from remote warehouse

Expected delivery Aug 12 - 25

Our customers say:

14-day return policy in accordance with European consumer protection law
Top ranking on Trustpilot
Add to your iMusic wish list

Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples - Wiley Series in Computational Statistics

* 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 July 16, 2010
ISBN13 9780470748268
Publishers John Wiley & Sons Inc
Pages 384
Dimensions 233 × 159 × 26 mm   ·   724 g
Language English  

See all of Liang, Faming (Texas A&M University, USA) ( e.g. Hardcover Book )