Advanced Markov Chain Monte Carlo Methods

Name: Advanced Markov Chain Monte Carlo Methods
Brand: John Wiley & Sons Inc
SKU: 9780470748268
Price: 456.59 PLN
Availability: InStock

Learning from Past Samples

Autor: Liang

Język:

Oprawa: Twarda

Wydawca: John Wiley & Sons Inc

Dostępność: Dostępna u dostawcy

Wysyłamy za 10-18 dni

456.59 zł

Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific computing. This...

Informacje o książce

Autor

Liang

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2010

strony

378

EAN

9780470748268

ISBN

0470748265

Enbook ID

04380235

Wydawca

John Wiley & Sons Inc

Waga

724

Wymiary

233 x 159 x 26

Pełny opis

Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific computing. This book discusses recent developments of MCMC methods with an emphasis on those making use of past sample information during simulations. The application examples are drawn from diverse fields such as bioinformatics, machine learning, social science, combinatorial optimization, and computational physics. 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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Advanced Markov Chain Monte Carlo Methods

Learning from Past Samples

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