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Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory - Morris H. (Carnegie-Mellon University DeGroot - Bog

Bag om Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory

Set that includes three works covering statistical decision theory and analysis The three books within this set are Optimal Statistical Decisions, Bayesian Inference in Statistical Analysis, and Applied Statistical Decision Theory. Optimal Statistical Decisions discusses the theory and methodology of decision-making in the field. The volume stands as a clear introduction to Bayesian statistical decision theory. A second book, Bayesian Inference in Statistical Analysis, examines the application and relevance of Bayes' theorem to problems that occur during scientific investigations, where inferences must be made regarding parameter values about which little is known. Key aspects of the Bayesian approach are discussed, including the choice of prior distribution, the problem of nuisance parameters, and the role of sufficient statistics. Applied Statistical Decision Theory covers the development of analytic techniques in the field of statistical decision theory. This classic book was first published in the 1960s.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9780471687887
  • Indbinding:
  • Paperback
  • Sideantal:
  • 1476
  • Udgivet:
  • 15. august 2006
  • Udgave:
  • Størrelse:
  • 158x234x28 mm.
  • Vægt:
  • 721 g.
  • Ukendt - mangler pt..

Normalpris

  • BLACK NOVEMBER

Medlemspris

Prøv i 30 dage for 45 kr.
Herefter fra 79 kr./md. Ingen binding.

Beskrivelse af Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory

Set that includes three works covering statistical decision theory and analysis The three books within this set are Optimal Statistical Decisions, Bayesian Inference in Statistical Analysis, and Applied Statistical Decision Theory. Optimal Statistical Decisions discusses the theory and methodology of decision-making in the field. The volume stands as a clear introduction to Bayesian statistical decision theory. A second book, Bayesian Inference in Statistical Analysis, examines the application and relevance of Bayes' theorem to problems that occur during scientific investigations, where inferences must be made regarding parameter values about which little is known. Key aspects of the Bayesian approach are discussed, including the choice of prior distribution, the problem of nuisance parameters, and the role of sufficient statistics. Applied Statistical Decision Theory covers the development of analytic techniques in the field of statistical decision theory. This classic book was first published in the 1960s.

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