View in EDS PDF Full Text

Bayesian Decision Analysis : Principles and Practice

Saved in:
Bibliographic Details
Title: Bayesian Decision Analysis : Principles and Practice
Description: 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.
Authors: Jim Q. Smith
Resource Type: eBook.
Subjects: Bayesian statistical decision theory
Categories: MATHEMATICS / Probability & Statistics / Bayesian Analysis
Database: eBook Collection (EBSCOhost)
FullText Links:
  – Type: ebook-pdf
Text:
  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 347827
RelevancyScore: 1031
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1031.17456054688
IllustrationInfo
ImageInfo – Size: thumb
  Target: https://rps2images.ebscohost.com/rpsweb/othumb?id=NL$347827$PDF&s=r
– Size: medium
  Target: https://rps2images.ebscohost.com/rpsweb/othumb?id=NL$347827$PDF&s=d
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Bayesian Decision Analysis : Principles and Practice
– Name: Abstract
  Label: Description
  Group: Ab
  Data: 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.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Jim+Q%2E+Smith%22">Jim Q. Smith</searchLink>
– Name: TypePub
  Label: Resource Type
  Group: TypPub
  Data: eBook.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Bayesian+statistical+decision+theory%22">Bayesian statistical decision theory</searchLink>
– Name: SubjectBISAC
  Label: Categories
  Group: Su
  Data: <searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Probability+%26+Statistics+%2F+Bayesian+Analysis%22">MATHEMATICS / Probability & Statistics / Bayesian Analysis</searchLink>
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=347827
RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 519.542
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Bayesian statistical decision theory
        Type: general
    Titles:
      – TitleFull: Bayesian Decision Analysis : Principles and Practice
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Jim Q. Smith
      – PersonEntity:
          Name:
            NameFull: Jim Q. Smith
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2010
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9780521764544
            – Type: isbn-electronic
              Value: 9780511860355
          Titles:
            – TitleFull: Bayesian Decision Analysis : Principles and Practice
              Type: main
ResultId 1