Items related to Bayesian Statistics: An Introduction
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. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS (Bayesian Inference Using Gibbs Sampling), now the standard computational tool for such numerical work. Other updates include new material on generalized linear modeling and Bernardo's theory of reference points.
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From the Publisher:
This new edition of Lee's popular book introduces the Bayesian philosophy of statistics. It has been completely updated and features new chapters on Gibbs sampling and hierarchical methods and more exercises.
From the Back Cover:
Bayesian Statistics is the school of thought that uses all information surrounding the likelihood of an event rather than just that collected experimentally. Among statisticians the Bayesian approach continues to gain adherents and 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. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS (Bayesian Inference Using Gibbs Sampling) as this is now the standard computational tool for such numerical work. Other alterations include new material on generalized linear modelling and Bernardo’s theory of reference points.
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- PublisherWiley
- Publication date2004
- ISBN 10 047068920X
- ISBN 13 9780470689202
- BindingPaperback
- Edition number3
- Number of pages351
- Rating
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Bayesian Statistics: An Introduction
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Bayesian Statistics: An Introduction
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(2004)
ISBN 10: 047068920X
ISBN 13: 9780470689202
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