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.
"synopsis" may belong to another edition of this title.
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.
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.
"About this title" may belong to another edition of this title.
Seller: Anybook.com, Lincoln, United Kingdom
Condition: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Book contains pen markings. In poor condition, suitable as a reading copy. Library sticker on front cover. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780470689202. Seller Inventory # 3983370
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