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The Resource Bayesian decision analysis : principles and practice, Jim Q. Smith

Bayesian decision analysis : principles and practice, Jim Q. Smith

Creator
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"--Provided by publisher
Language
eng
Work
Publication
Extent
1 online resource (ix, 338 pages)
Contents
  • 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
Isbn
9786612941887
Link
http://libproxy.rpi.edu/login?url=http://app.knovel.com/hotlink/toc/id:kpBDAPP001/bayesian-decision-analysis
Instance
Label
Bayesian decision analysis : principles and practice
Title
Bayesian decision analysis
Title remainder
principles and practice
Statement of responsibility
Jim Q. Smith
Creator
Subject
Language
eng
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"--Provided by publisher
Cataloging source
DLC
Illustrations
illustrations
Index
index present
LC call number
QA279.5
LC item number
.S628 2010
Literary form
non fiction
Nature of contents
bibliography
Bayesian decision analysis : principles and practice, Jim Q. Smith
Label
Bayesian decision analysis : principles and practice, Jim Q. Smith
Link
http://libproxy.rpi.edu/login?url=http://app.knovel.com/hotlink/toc/id:kpBDAPP001/bayesian-decision-analysis
Publication
Related Contributor
Related Location
Related Agents
Related Authorities
Related Subjects
Antecedent source
unknown
Bibliography note
Includes bibliographical references (pages 322-334) and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
mixed
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9786612941887&userID=ebsco-test&password=ebsco-test
Dimensions
unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b3128897'}
Extent
1 online resource (ix, 338 pages)
File format
unknown
Form of item
online
Isbn
9786612941887
Lccn
2010031690
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote

Subject

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