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Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) Hardcover – May 10, 2006

ISBN-13: 978-1584885870 ISBN-10: 1584885874 Edition: 2nd

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Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) + Markov Chain Monte Carlo in Practice (Chapman & Hall/CRC Interdisciplinary Statistics) + Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
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Product Details

  • Series: Chapman & Hall/CRC Texts in Statistical Science (Book 68)
  • Hardcover: 344 pages
  • Publisher: Chapman and Hall/CRC; 2 edition (May 10, 2006)
  • Language: English
  • ISBN-10: 1584885874
  • ISBN-13: 978-1584885870
  • Product Dimensions: 9.5 x 6.1 x 0.9 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #380,623 in Books (See Top 100 in Books)

Editorial Reviews

Review

… one of the most comprehensive and readable texts on stochastic simulation using the technique of Markov chain Monte Carlo. … this second edition has been extensively updated to include the recent literature. New sections on spatial modeling and model adequacy have now been included, together with more illustrative material. Many of the computer codes written in R and WinBUGS … are available for download from the web. This enhances the utility of the book, both as a reference for researchers and a text on modern Bayesian computation and Bayesian inference courses for students.
-C.M. O'Brien (CEFAS Lowestoft Laboratory, UK), Short Book Reviews

Read the reviews of the bestselling first edition:
...a must for every research library, and should be given serious consideration for use as a graduate text
-Short Book Reviews of the ISI

…nicely focused, elementary-level coverage…makes this book a suitable choice for an introductory course.
-Journal of the ASA, March, 2000

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Customer Reviews

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Most Helpful Customer Reviews

6 of 6 people found the following review helpful By Engineer Always Learning on October 13, 2012
Format: Hardcover Verified Purchase
I have several negative comments before a full review and these apply to the first edition of their text. First, most of Chapter 4 (sections 4.1 - 4.5) is lifted from Chapters 1 and 2 of Hoel, Port, and Stone (1972) and reorganized without any attribution - even the notation and examples are the same. I find this offensive. Second, they could really use an English-speaking editor to clean up the way the text reads, I can't name the number of times I saw "highly dimensional distributions" and other annoying English. The editor of this book should be fired, if there was one. Of course, in the Preface it does state "The book grew out of lecture notes in Portuguese prepared for a short course on the topic taught at the XII Meeting of Brazilian Statisticians and Probabilists, held in Caxambu (MG) in August 1996." Consider yourself warned.

That said, the book is informative, with the following major outline:
Chapter 1: Stochastic Simulation
Chapter 2: Bayesian Inference
Chapter 3: Approximate Methods of Inference
Chapter 4: Markov Chains
Chapter 5: Gibbs Sampling
Chapter 6: Metropolis-Hastings Algorithms
Chapter 7: Further Topics in MCMC

The first three chapters are informative, but you won't learn the theory for the first time from this text. Chapter 4 focuses primarily on discrete parameter, discrete sample space Markov processes - Markov chains. It's not as clear as the original Hoel, Port, and Stone from which it has been lifted and reorganized. It is useful as review if you already have a solid grasp of Markov chain theory.
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4 of 4 people found the following review helpful By C. Vladimir Rodríguez Caballero on December 2, 2011
Format: Hardcover
If you are a Bayesian statistician or maybe if you want to understand this statistical paradigm, this book is not only necessary but indispensable. Professor Gamerman and Lopes present an excellent study about the simulation techniques that we need to implement if we want to draw samples from posterior distribution when we don't have this in a closed way. This book brilliantly analyzes the most basic MCMC methods like Gibbs Sampler and Metropolis Hastings, on the other hand the reader shall find a lot of funny examples and some applications.
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2 of 3 people found the following review helpful By Vishnu Sreekumar on January 8, 2014
Format: Hardcover Verified Purchase
I am a fifth year graduate student in Psychology. I was assigned this book as part of my readings for candidacy. I also had this book for a seminar course on Bayesian methods. The first time I encountered this book during the course, I must admit that I found it difficult to read, so I ended up not being motivated enough to go through with all the assigned readings. I have taken 2 graduate level courses on Bayesian modeling. I have now finished reading 6 chapters of the book as part of preparing for my candidacy exam and I am glad I took another shot at reading this book. I now understand fairly well issues with MCMC, what the limitations of Gibbs sampling are, when Metropolis-Hastings is typically used and why convergence diagnostics theory is hard. All of these are important practical issues for anybody who wishes to use these methods in their work.

As other reviewers state, the writing can get dense sometimes. I skipped over some stuff that I felt was too much detail for my purposes and yet came away with a certain level of confidence about the knowledge I gained from the book. If you are ready to work out some of the derivations yourself and if you are willing to attempt to solve some of the exercises (which I did in my grad level class), you will get the most out of this book.

So in conclusion, this is a must read for anybody serious about understanding Bayesian methods but this shouldn't be the first book you read on the topic. I ordered this book today because my library copy is overdue and I would like to have this book in my personal library.
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0 of 2 people found the following review helpful By Rich on May 23, 2012
Format: Hardcover Verified Purchase
This is an excellent book. It describes the material clearly, using plenty of cogent examples. I gladly recccomend this book.
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11 of 22 people found the following review helpful By Beloved Charles on February 14, 2009
Format: Hardcover Verified Purchase
This book is very self-contained and provides intuitive explanations and illuminating examples. Very good for self-study.
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