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Bayesian statistics : an introduction

Author: Peter M Lee
Publisher: London : Arnold ; New York : Wiley, 2004.
Edition/Format:   Print book : English : 3rd edView all editions and formats
Summary:
Among statisticians the Bayesian approach continues to gain adherents and this new edition of Peter Lee's classic introduction maintains the clarity of exposition and use of examples for which the text is known and praised. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS, as this is now the standard computational tool for such numerical work.  Read more...
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Document Type: Book
All Authors / Contributors: Peter M Lee
ISBN: 0340814055 9780340814055 9780470689202 047068920X
OCLC Number: 54888001
Description: 351 pages : illustrations ; 24 cm
Contents: 1. Preliminaries --
2. Bayesian inference for the normal distribution --
3. Some other common distributions --
4. Hypothesis testing --
5. Two-sample problems --
6. Correlation, regression and the analysis of variance --
7. Other topics --
8. Hierarchical models --
9. Gibbs sampler and other numerical methods.
Responsibility: Peter M. Lee.
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Abstract:

This new edition of Peter Lee's well-established introduction maintains the clarity of exposition and use of examples for which this text is known and praised.  Read more...

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Lee's book provides a reasonable introduction to Bayesian statistics - December 2004 -- Significance - the Royal Statistical Society Maga

 
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