- Paperback: 360 pages
- Publisher: Hodder Arnold; 2nd Revised edition edition (26 Sep 1997)
- Language English
- ISBN-10: 0340677856
- ISBN-13: 978-0340677858
- Product Dimensions: 23.2 x 15.8 x 2.1 cm
- Amazon Bestsellers Rank: 1,438,008 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Lee's book provides a reasonable introduction to Bayesian statistics - December 2004 (Significance - the Royal Statistical Society Maga )
--This text refers to an out of print or unavailable edition of this title.
Product Description
Thoroughly updated and expanded, this successful introduction to the subject includes a new chapter on hierarchical methods in Bayesian statistics and gives a fuller treatment of empirical Bayes methods. It also includes a chapter on real numerical methods, especially the EM algorithm and Gibbs sampling, and a description of Bayes linear methods.
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The notation will be kept as simple as possible, but it is useful to express statements about probability in the language of set theory. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
The notation will be kept as simple as possible, but it is useful to express statements about probability in the language of set theory. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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65 of 65 people found the following review helpful
Good introduction to basic theory of Bayesian statistics
4 Dec 2001
Format:Paperback
This is a simple and easy-to-read introduction to the basics of Bayesian statistics, for someone with some previous exposure to statistical methods and theory. Lee does not try to do too much with this book. It's not too taxing on the brain, uses simple and easy-to-follow notation, and has a helpful appendix of common statistical distributions. I like the emphasis on conjugate priors, which are the mathematically most tractable Bayesian models that are often not treated fully in other texts. (Someone still needs to write the definitive text on conjugate Bayesian models.)
The book is limited in scope, a strength if you're just getting started on this topic, but will frustrate once you get into this stuff. There are plenty of other good books that go beyond the basics once you're ready.
25 of 26 people found the following review helpful
good intermediate text
22 Jan 2008
Format:Paperback
Although only the second edition is listed, I have read only the first 1989 edition and my review is for that edition. Lee wrote this book with the goal of teaching an introductory course in Bayesian statistics to his students at York University. He wanted a text that was more mathematical and deatiled than Lindley (1965) but not quite at the level of Box and Tiao.
This text achieves that goal. It was published at the time when MCMC methods were only starting to be appreciated. So the wider use of general prior distributions and hierarchical models does not yet enter into this book. I would assume that the second edition published in 1997 was written to remedy this shortcoming but I have not seen if it does.
But for the time it was a good intermediate text.
This text achieves that goal. It was published at the time when MCMC methods were only starting to be appreciated. So the wider use of general prior distributions and hierarchical models does not yet enter into this book. I would assume that the second edition published in 1997 was written to remedy this shortcoming but I have not seen if it does.
But for the time it was a good intermediate text.
18 of 18 people found the following review helpful
a review
17 Sep 2006
Format:Paperback
This book has a clean selection of materials as an introduction to bayesian statistics. It is quite readable. Two problems however: 1) the formula derivation and reasoning often have intermediate steps skipped. You need to think for a while for derivations and his texts. In particular, you need to figure out by yourself which theorem or previous results that the derivation is based on. 2) typos. the 3rd printing still has typos not listed in the author's page, not too many but not trivial either.
Anyway, I still recommand this book because no better introductory bayesian book found yet.
Anyway, I still recommand this book because no better introductory bayesian book found yet.
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