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Advanced Markov Chain Monte Carlo Methods – Learning From Past Samples de F Liang

Advanced Markov Chain Monte Carlo Methods – Learning From Past Samples: Wiley Series in Computational Statistics

Autor F Liang
en Limba Engleză Hardback – 15 iul 2010
* 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.
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Specificații

ISBN-13: 9780470748268
ISBN-10: 0470748265
Pagini: 378
Dimensiuni: 152 x 229 x 22 mm
Greutate: 0.68 kg
Editura: Wiley
Seria Wiley Series in Computational Statistics

Locul publicării:Chichester, United Kingdom

Public țintă

Researchers specializing in Monte Carlo Algorithms, Scientists interested in using Monte Carlo method and graduate students in statistics, computational biology, engineering, and computer sciences who want to learn Monte Carlo methods. Researchers in operations research, simulation and computational statistics.

Notă biografică

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.