Bayesian Decision Analysis
Principles and Practice
Format:Hardback
Publisher:Cambridge University Press
Published:23rd Sep '10
Currently unavailable, and unfortunately no date known when it will be back
A textbook and guide to conducting Bayesian decision analysis of sometimes very complex policies and collaborative decisions.
Real-world decisions involve numbers, but they also involve people. Bayesian decision analysis gives a principled framework for reconciling the two. This textbook explains how to use statistical theory, psychology and algorithms to guide decision makers so that they can marshal available evidence and defend their actions.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.
'The author presents a good set of solved exercises, which serve for illustration, and a large set of proposed exercises are suggested. I recommend this book for professional and advanced students in statistics, operations research, computer science, artificial intelligence, cognitive sciences and different branches of engineering.' Narciso Bouza Herrera, Zentralblatt MATH
'… an excellent resource for students at final year undergraduate level or higher, and for anyone researching issues of complex decision-making.' Mathematics Today
ISBN: 9780521764544
Dimensions: 255mm x 180mm x 21mm
Weight: 840g
348 pages