Applied Statistical Decision Theory
Title | Applied Statistical Decision Theory PDF eBook |
Author | Howard Raiffa |
Publisher | |
Pages | 356 |
Release | 1966 |
Genre | |
ISBN |
Applied Statistical Decision Theory
Title | Applied Statistical Decision Theory PDF eBook |
Author | Howard Raiffa |
Publisher | Harvard Business Review Press |
Pages | 394 |
Release | 1961 |
Genre | Business & Economics |
ISBN |
"In the field of statistical decision theory, Raiffa and Schlaifer have sought to develop new analytic techniques by which the modern theory of utility and subjective probability can actually be applied to the economic analysis of typical sampling problems." --From the foreword to their classic work "Applied Statistical Decision Theory," First published in the 1960s through Harvard University and MIT Press, the book is now offered in a new paperback edition from Wiley
Statistical Decision Theory
Title | Statistical Decision Theory PDF eBook |
Author | James Berger |
Publisher | Springer Science & Business Media |
Pages | 440 |
Release | 2013-04-17 |
Genre | Mathematics |
ISBN | 147571727X |
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.
Statistical Decision Theory and Bayesian Analysis
Title | Statistical Decision Theory and Bayesian Analysis PDF eBook |
Author | James O. Berger |
Publisher | Springer Science & Business Media |
Pages | 633 |
Release | 2013-03-14 |
Genre | Mathematics |
ISBN | 147574286X |
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.
Applied Statistical Decision Theory
Title | Applied Statistical Decision Theory PDF eBook |
Author | Howard Raiffa |
Publisher | |
Pages | |
Release | 1974 |
Genre | |
ISBN |
Introduction to Statistical Decision Theory
Title | Introduction to Statistical Decision Theory PDF eBook |
Author | John Winsor Pratt |
Publisher | |
Pages | 875 |
Release | 1994 |
Genre | Statistical Decision |
ISBN |
Asymptotic Methods in Statistical Decision Theory
Title | Asymptotic Methods in Statistical Decision Theory PDF eBook |
Author | Lucien Le Cam |
Publisher | Springer Science & Business Media |
Pages | 767 |
Release | 2012-12-06 |
Genre | Mathematics |
ISBN | 1461249465 |
This book grew out of lectures delivered at the University of California, Berkeley, over many years. The subject is a part of asymptotics in statistics, organized around a few central ideas. The presentation proceeds from the general to the particular since this seemed the best way to emphasize the basic concepts. The reader is expected to have been exposed to statistical thinking and methodology, as expounded for instance in the book by H. Cramer [1946] or the more recent text by P. Bickel and K. Doksum [1977]. Another pos sibility, closer to the present in spirit, is Ferguson [1967]. Otherwise the reader is expected to possess some mathematical maturity, but not really a great deal of detailed mathematical knowledge. Very few mathematical objects are used; their assumed properties are simple; the results are almost always immediate consequences of the definitions. Some objects, such as vector lattices, may not have been included in the standard background of a student of statistics. For these we have provided a summary of relevant facts in the Appendix. The basic structures in the whole affair are systems that Blackwell called "experiments" and "transitions" between them. An "experiment" is a mathe matical abstraction intended to describe the basic features of an observational process if that process is contemplated in advance of its implementation. Typically, an experiment consists of a set E> of theories about what may happen in the observational process.