Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)
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Publication
2001-10-05 - Springer
Language
English
Word Count
96,500 words, Guess
Page Count
386 pages
Identifiers
- Open LibraryOL7449876M
- ISBN-139780387989358
- ISBN-100387989358
- OCLC Control Number42389604
- Library of Congress Control Number99046366
and 2 more
- LibraryThing5164724
- Goodreads4424278
Classifications
- LCCQA279.5 .C57 2000
Description
"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 summaries from a given MCMC sample.". "The book presents and equal mixture of theory and applications involving real data. It is intended as a graduate textbook or a reference book for a one-semester course at the advanced master's or Ph.D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners."--BOOK JACKET.
First Sentence
There are two major challenges involved in advanced Bayesian computation.
Subjects
Other Editions
- Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)
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