Bayesian decision analysis : principles and practice

著者

書誌事項

Bayesian decision analysis : principles and practice

Jim Q. Smith

Cambridge University Press, 2010

大学図書館所蔵 件 / 全13件

この図書・雑誌をさがす

注記

Includes bibliographical references (p. 322-334) and index

内容説明・目次

内容説明

Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis of simple decision problems to a careful analysis of the sometimes very complex and data rich structures confronted by practitioners. The book contains basic material on subjective probability theory and multi-attribute utility theory, event and decision trees, Bayesian networks, influence diagrams and causal Bayesian networks. The author demonstrates when and how the theory can be successfully applied to a given decision problem, how data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be implemented. Evolving from a third-year undergraduate course taught by the author over many years, all of the material in this book will be accessible to a student who has completed introductory courses in probability and mathematical statistics.

目次

  • Preface
  • Part I. Foundations of Decision Modeling: 1. Introduction
  • 2. Explanations of processes and trees
  • 3. Utilities and rewards
  • 4. Subjective probability and its elicitation
  • 5. Bayesian inference for decision analysis
  • Part II. Multi-Dimensional Decision Modeling: 6. Multiattribute utility theory
  • 7. Bayesian networks
  • 8. Graphs, decisions and causality
  • 9. Multidimensional learning
  • 10. Conclusions
  • Bibliography.

「Nielsen BookData」 より

詳細情報

ページトップへ