Dani Gamerman, Hedibert F. Lopes

Markov Chain Monte Carlo (eBook, ePUB)

Stochastic Simulation for Bayesian Inference, Second Edition

• Format: ePub

Produktbeschreibung

Incorporating changes in theory and highlighting new applications, this book presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. This second edition includes many new examples in the chapters on Gibbs sampling and Metropolis-Hastings algorithms. It incorporates all the recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection. It also features many worked examples and discusses computation using both R and WinBUGS. With additional exercises and selected solutions within the text, it offers all data sets and software for download from the Web.

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Produktdetails

• Verlag: Taylor & Francis
• Erscheinungstermin: 10. Mai 2006
• Englisch
• ISBN-13: 9781040075623
• Artikelnr.: 72518843

Autorenporträt

Dani Gamerman, Hedibert F. Lopes