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...

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Bibliographic Details
Main Author: Smith, J. Q., 1953-
Format: eBook
Language: English
Published: Cambridge ; New York : Cambridge University Press, 2010.
Subjects:
Bayesian statistical decision theory.
elektronické knihy
electronic books
ISBN: 9780511860355
0511860358
9780511857744
0511857748
9780511856006
0511856008
0511856873
9780511856877
9780511779237
0511779232
9786612941887
661294188X
9780521764544
0521764548
Physical Description: 1 online resource (ix, 338 pages) : illustrations

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Table of contents

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100 1 |a Smith, J. Q.,  |d 1953-  |1 https://id.oclc.org/worldcat/entity/E39PCjMHbRrpVT6xPqyYRGBRXd 
245 1 0 |a Bayesian decision analysis :  |b principles and practice /  |c Jim Q. Smith. 
260 |a Cambridge ;  |a New York :  |b Cambridge University Press,  |c 2010. 
300 |a 1 online resource (ix, 338 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a "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"--Provided by publisher 
504 |a Includes bibliographical references (pages 322-334) and index. 
505 0 |a Foundations of decision modeling. Introduction -- 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. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Bayesian statistical decision theory. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |a Smith, J.Q., 1953-  |t Bayesian decision analysis.  |d Cambridge, UK ; New York : Cambridge University Press, 2010  |z 9780521764544  |w (DLC) 2010031690  |w (OCoLC)619125102 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpBDAPP001/bayesian-decision-analysis?kpromoter=marc  |y Full text 

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