TY  - BOOK
AU  - Smith,J.Q.
TI  - Bayesian decision analysis: principles and practice 
SN  - 9780511779237 (ebook)
AV  - QA279.5 .S628 2010
U1  - 519.5/42 22
PY  - 2010///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Bayesian statistical decision theory
N1  - Title from publisher's bibliographic system (viewed on 05 Oct 2015); Machine generated contents note: 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
N2  - 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
UR  - https://doi.org/10.1017/CBO9780511779237
ER  -