05137nam 2200685 a 450 991101892120332120200520144314.09786612307669978128230766712823076659780470317105047031710897804703179450470317949(CKB)1000000000807596(EBL)469810(OCoLC)587388980(SSID)ssj0000343357(PQKBManifestationID)11231094(PQKBTitleCode)TC0000343357(PQKBWorkID)10290932(PQKB)10626247(MiAaPQ)EBC469810(PPN)159302277(Perlego)2776634(EXLCZ)99100000000080759620030313d2003 uy 0engur|n|---|||||txtccrSubjective and objective Bayesian statistics principles, models, and applications /S. James Press ; with contributions by Siddhartha Chib ... [et al.]2nd ed.Hoboken, N.J. Wiley-Intersciencec20031 online resource (591 p.)Wiley series in probability and statisticsDescription based upon print version of record.9780471348436 0471348430 Includes bibliographical references and index.Subjective and Objective Bayesian Statistics Principles, Models, and Applications; CONTENTS; Preface; Preface to the First Edition; A Bayesian Hall of Fame; PART I. FOUNDATIONS AND PRINCIPLES; 1. Background; 1.1 Rationale for Bayesian Inference and Prelirmnary Views of Bayes' Theorem; 1.2 Example: Observing a Desired Experimental Effect; 1.3 Thomas Bayes; 1.4 Brief Descriptions of the Chapters; summary; Exercises; Further Reading; 2. A Bayesian Perspective on Probability; 2.1 Introduction; 2.2 Types of Probability; 2.2.1 Axiom Systems; 2.2.2 Frequency and Long-Run Probability2.2.3 Logical Probability2.2.4 Kolmogorov Axiom System of Frequency Probability; 2.2.5 Savage System of Axioms of Subjective Probability; 2.2.6 Rényi Axiom System of Probability; 2.3 Coherence; 2.3.1 Example of Incoherence; 2.4 Operationalizing Subjective Probability Beliefs; 2.4.1 Example of Subjective Probability Definition and Operationalization; 2.5 Calibration of Probability Assessors; 2.6 Comparing Probability Definitions; Summary; Complement to Chapter 2 The Axiomatic Foundation of Decision making of L. J. Savage; Utility Functions; Exercises; Further Reading3. The Likelihood Function3.1 Introduction; 3.2 Likelihood Function; 3.3 Likelihood Principle; 3.4 Likelihood Principle and Conditioning; 3.5 Likelihood and Bayesian Inference; 3.6 Development of the Likelihood Function Using Histograms and Other Graphical Methods; summary; Exercises; Further Reading; 4. Bayeds' Theorem; 4.1 Introduction; 4.2 General Form of Bayes' Theorem for Events; 4.2.1 Bayes' Theorem for Complementary Events; 4.2.2 Prior Probabilities; 4.2.3 Posterior Probabilities; 4.2.4 Odds Ratios; Example 4.1 Bayes' Theorem for Events: DNA Fingerprinting4.3 Bayes' Theorem for Discrete Data and Discrete Parameter4.3.1 Interpretation of Bayes' Theorem for Discrete Data and Discrete Parameter; Example 4.2 Quality Control in Manufacturing: Discrete Data and Discrete Parameter (Inference About a Proportion); 4.3.2 Bayes' Theorem for Discrete Data and Discrete Models; 4.4 Bayes' Theorem for Continuous Data and Discrete Parameter; 4.4.1 Interpretation of Bayes' Theorem for Continuous Data and Discrete ParameterExample 4.3 Infming the Section of a Class from which Student was Selected: Continuous Data and Discrcte Parameter (Choosing from a Discrete Set of Models)4.5 Bayes' Theorem for Discrete Data and Continuous Parameter; Example 4.4 Quality Control in Manufacturing: Discrete Data and Continuous Parameter; 4.6 Baycs' Theorem for Continuous Data and Continuous Parameter; Example 4.5 Normal Data: Unknown Mean, Known Variance; Example 4.6 Normal Data: Unknown Mean, Unknown Variance; Summary; Exercises; Further Reading; Complement to Chapter 4: Heights of the Standard Normal Density5. Prior DistributionsShorter, more concise chapters provide flexible coverage of the subject.Expanded coverage includes: uncertainty and randomness, prior distributions, predictivism, estimation, analysis of variance, and classification and imaging.Includes topics not covered in other books, such as the de Finetti Transform.Author S. James Press is the modern guru of Bayesian statistics.Wiley series in probability and statistics.Bayesian statistical decision theoryBayesian statistical decision theory.519.5/42Press S. James280166MiAaPQMiAaPQMiAaPQBOOK9911018921203321Subjective and objective Bayesian statistics4416579UNINA