The Bayesian choice : a decision-theoretic motivation

著者

書誌事項

The Bayesian choice : a decision-theoretic motivation

Christian P. Robert

（Springer texts in statistics）

Springer-Verlag, 1996, c1994

Corr. 2nd print

  • : us
  • : gw

タイトル別名

Analyse statistique bayésienne

大学図書館所蔵 件 / 全5件

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注記

Includes bibliographical references (p. [395]-415) and indexes

内容説明・目次

巻冊次

: us ISBN 9780387942964

内容説明

This graduate-level textbook presents an introduction to Bayesian statistics and decision theory. Its scope covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, the Stein effect, hierarchical and empirical Bayes modeling, Monte Carlo integration, and Gibbs sampling. It is the translation of a successful French text. In the translation to the English edition, the author has taken the opportunity to add and update material, and to include many problems and exercises for students. From reviews of the French edition: I strongly encourage everyone teaching Bayesian decision theory to use (this) as the main textbook. Journal of the American Statisical Association On the whole, the book serves its purpose admirably. Journal of the Royal Statistical Society
巻冊次

: gw ISBN 9783540942962

内容説明

This graduate-level textbook presents an introduction to Bayesian statistics and decision theory. Its scope covers both the basic ideas of statistical theory, but also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, Stein effects, hierarchical and empirical modelling, and Gibbs sampling. It is the translation of a successful French text. In the translation to the English edition, the author has taken the opportunity to add and update material, and to include many problems and exercises for students.

目次

Contents: Introduction.- Decision-Theoretic Foundations of Statistical Inference.- From Prior Information to Prior Distributions.- Bayesian Point Estimation.- Tests and Confidence Regions.- Admissibility and Complete Classes.- Invariance, Haar Measures, and Equivariant Estimators.- Hierarchical and Empirical Bayes Extensions.- Bayesian Calculations.- A Defense of the Bayesian Choice.

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