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Field name	Details
Dewey Class	519
Title	Statistical Decision Theory ([EBook] :) : Foundations, Concepts, and Methods / / by James O. Berger.
Author	Berger, James O.
Other name(s)	SpringerLink (Online service)
Publication	New York, NY : : Springer New York : : Imprint: Springer, , 1980.
Physical Details	XV, 428 p. : online resource.
Series	Springer Series in Statistics 0172-7397
ISBN	9781475717273
Summary Note	Decision theory is generally taught in one of two very different ways. When of opti taught by theoretical statisticians, it tends to be presented as a set of mathematical techniques mality principles, together with a collection of various statistical procedures. When useful in establishing the optimality taught by applied decision theorists, it is usually a course in Bayesian analysis, showing how this one decision principle can be applied in various practical situations. The original goal I had in writing this book was to find some middle ground. I wanted a book which discussed the more theoretical ideas and techniques of decision theory, but in a manner that was constantly oriented towards solving statistical problems. In particular, it seemed crucial to include a discussion of when and why the various decision prin ciples should be used, and indeed why decision theory is needed at all. This original goal seemed indicated by my philosophical position at the time, which can best be described as basically neutral. I felt that no one approach to decision theory (or statistics) was clearly superior to the others, and so planned a rather low key and impartial presentation of the competing ideas. In the course of writing the book, however, I turned into a rabid Bayesian. There was no single cause for this conversion; just a gradual realization that things seemed to ultimately make sense only when looked at from the Bayesian viewpoint.:
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. Technical Arguments from Chapter 4 -- I. Verification of Formulas (4.6) through (4.8) -- II. Verification of Formula (4.10) -- III. Verification of Formula (4.12) -- 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/10.1007/978-1-4757-1727-3
Links to Related Works	Subject References: Applications of Mathematics . Applied mathematics . Engineering mathematics . Mathematics . Authors: Berger, James O. . Corporate Authors: SpringerLink (Online service) . Series: Springer Series in Statistics . Classification: 519 .

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Statistical Decision Theory: Foundations, Concepts, and Methods /

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