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Feldname	Details
Dewey Class	519.5
Titel	Statistical Decision Theory and Bayesian Analysis ([EBook] /) / by James O. Berger.
Verfasser	Berger, James O.
Other name(s)	SpringerLink (Online service)
Edition statement	Second Edition.
Veröffentl	New York, NY : : Springer New York : : Imprint: Springer, , 1985.
Physical Details	XVI, 618 p. : online resource.
Reihe	Springer Series in Statistics 0172-7397
ISBN	9781475742862
Summary Note	In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.:
Contents note	1 Basic Concepts -- 2 Utility and Loss -- 3 Prior Information and Subjective Probability -- 4 Bayesian Analysis -- 5 Minimax Analysis -- 6 Invariance -- 7 Preposterior and Sequential Analysis -- 8 Complete and Essentially Complete Classes -- Appendix 1 Common Statistical Densities -- I Continuous -- II Discrete -- Appendix 2 Supplement to Chapter 4 -- II Development of (4.121) and (4.122) -- III Verification of Formula (4.123) -- Appendix 3 Technical Arguments from Chapter 7 -- I Verification of Formula (7.8) -- II Verification of Formula (7.10) -- Notation and Abbreviations -- Author Index.
System details note	Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site	http://dx.doi.org/10.1007/978-1-4757-4286-2
LINKS ZU 'VERWANDTEN WERKEN	Schlagwörter: . Statistical Theory and Methods . Statistics . Authors: Berger, James O. . Corporate Authors: SpringerLink (Online service) . Series: Springer Series in Statistics . Classification: 519.5 .

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Statistical Decision Theory and Bayesian Analysis

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