Bayesian decision analysis: principles and practice
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 mater...
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| Main Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2010
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| Links: | https://doi.org/10.1017/CBO9780511779237 |
| Summary: | 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. |
| Physical Description: | 1 Online-Ressource (ix, 338 Seiten) |
| ISBN: | 9780511779237 |
Staff View
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| spelling | Smith, J. Q. 1953- Bayesian decision analysis principles and practice Jim Q. Smith Cambridge Cambridge University Press 2010 1 Online-Ressource (ix, 338 Seiten) txt c cr 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. Erscheint auch als Druck-Ausgabe 9780521764544 |
| spellingShingle | Smith, J. Q. 1953- Bayesian decision analysis principles and practice |
| title | Bayesian decision analysis principles and practice |
| title_auth | Bayesian decision analysis principles and practice |
| title_exact_search | Bayesian decision analysis principles and practice |
| title_full | Bayesian decision analysis principles and practice Jim Q. Smith |
| title_fullStr | Bayesian decision analysis principles and practice Jim Q. Smith |
| title_full_unstemmed | Bayesian decision analysis principles and practice Jim Q. Smith |
| title_short | Bayesian decision analysis |
| title_sort | bayesian decision analysis principles and practice |
| title_sub | principles and practice |
| work_keys_str_mv | AT smithjq bayesiandecisionanalysisprinciplesandpractice |