Monte Carlo Methods in Bayesian Computation

Language: English

Published by Springer New York Jan 2000, 2000

0387989358 / 9780387989358

Series: Book 49 of 160 - Springer Series in Statistics

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -This book examines advanced Bayesian computational methods. It presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo methods for estimation of posterior quantities, improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. The authors also discuss computions involving model comparisons, including both nested and non-nested models, marginal likelihood methods, ratios of normalizing constants, Bayes factors, the Savage-Dickey density ratio, Stochastic Search Variable Selection, Bayesian Model Averaging, the reverse jump algorithm, and model adequacy using predictiveand latent residual approaches. The book presents an equal mixture of theory and applications involving real data. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners. Ming-Hui Chen is Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute, Qu-Man Shao is Assistant Professor of Mathematics at the University of Oregon. Joseph G. Ibrahim is Associate Professor of Biostatistics at the Harvard School of Public Health and Dana-Farber Cancer Institute. 406 pp. Englisch.

Seller Inventory # 9780387989358

Title
Monte Carlo Methods in Bayesian Computation
Author
Ming-Hui Chen
Publisher
Springer New York Jan 2000
Publication year
2000
Condition
Neu
Binding
Buch
Language
English
ISBN 10
0387989358
ISBN 13
9780387989358
Edition
2nd Edition
Item weight
773 grams
Dimensions
241x160x27 mm
Series
Book 49 of 160: Springer Series in Statistics

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

Shipping rates from Germany to U.S.A.

Item5 to 15 business days5 to 15 business days
First itemUS$ 26.53US$ 26.53
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BuchWeltWeit Ludwig Meier e.K.

Germany