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Statistical Decision Theory and Bayesian Analysis

  • James O. Berger
Textbook

Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages i-xvi
    PDF
  2. Basic Concepts
    James O. Berger
    Pages 1-45
  3. Utility and Loss
    James O. Berger
    Pages 46-73
  4. Prior Information and Subjective Probability
    James O. Berger
    Pages 74-117
  5. Bayesian Analysis
    James O. Berger
    Pages 118-307
  6. Minimax Analysis
    James O. Berger
    Pages 308-387
  7. Invariance
    James O. Berger
    Pages 388-431
  8. Preposterior and Sequential Analysis
    James O. Berger
    Pages 432-520
  9. Complete and Essentially Complete Classes
    James O. Berger
    Pages 521-558
  10. Back Matter
    Pages 559-618
    PDF

About this book

Introduction

In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.

Keywords

Analysis Bayessches Verfahren Entscheidung (Math.) Excel decision theory

Authors and affiliations

  • James O. Berger
    • 1
  1. 1.Institute of Statistics and Decision SciencesDuke UniversityDurhamUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4757-4286-2
  • Copyright Information Springer-Verlag New York 1985
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-3074-3
  • Online ISBN 978-1-4757-4286-2
  • Series Print ISSN 0172-7397
  • Buy this book on publisher's site