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This is page 1Printer: Opaque thisLecture Notes on Bayesian Estimation andClassificationM ario A. T. Figueiredo,Instituto de Telecomunica c oes, andInstituto Superior T ecnico1049-001 LisboaPortugal(Email address: Copyright by the author. DO NOT 20042This is page 3Printer: Opaque thisContents1 Introduction to Bayesian Decision Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . Statistical Decision Theory . . . . . . . . . . . . . . . . . . Basic Elements . . . . . . . . . . . . . . . . . . . . . Frequentist Risk Function and Decision Rules . . . . Bayesian Decision Theory . . . . . . . . . . . . . . . . . . . Subjective Probabilities and Degrees of Belief . . . . A Posteriori Expected Loss and Bayesian Decisions . Bayes Risk . . . . . . . . . . . . . . . . . . . . . . . Admissibility of Bayesian Rules.)

10 1. Introduction to Bayesian Decision Theory Parameter estimation problems (also called point estimation problems), that is, problems in which some unknown scalar quantity (real valued) is to

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