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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. SHARE      | | | | or call in the US toll free 1-888-866-9150 product ID: 145950 |
To view this DRM protected ebook on your desktop or laptop you will need to have Adobe Digital Editions installed. It is a free software. We also strongly recommend that you sign up for an AdobeID at the Adobe website. For more details please see FAQ 1&2. To view this ebook on an iPhone, iPad or Android mobile device you will need the Readmill, BlueFire Reader, or Txtr app. These are free, too. For more details see this article. | Ebook Details |
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| Pages: | 348 |
| Size: | 2.1 MB |
| Publisher: | Cambridge University Press |
| Date published: | Sep 2010 |
| ISBN: | 9780511855153 |
| DRM Settings |
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| Copying: | of 5 selections every 30 days allowed | | Printing: | of 20 pages every 30 days allowed | | Read Aloud: | allowed |
This product is listed in the following categories:Non-Fiction > Mathematics > Probability & Statistics
Non-Fiction > Mathematics > Linear Programming
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