Smith J.Q. Bayesian Decision Analysis: Principles and Practice

Cambridge University Press, 2010. — 348 p. — ISBN: 0521764548, 9780521764544.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.Foundations of Decision Modeling:Explanations of processes and trees
Utilities and rewards
Subjective probability and its elicitation
Bayesian inference for decision analysis
Multi-Dimensional Decision Modeling:
Multiattribute utility theory
Bayesian networks
Graphs, decisions and causality
Multidimensional learning
Conclusions