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Bayesian Theory / Edition 1

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Chichester 2000 Hardcover Second printing Near Fine Hardbound, 586 pp., clean unmarked text, Near Fine copy, light soil or rubbing to the page-edges and the covers (specifically ... the tips and edges of the covers). Read more Show Less

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Overview

Bayesian Theory is the first volume of a related series of three and will be followed by Bayesian Computation, and Bayesian Methods. The series aims to provide an up-to-date overview of the why?, how? and what? of Bayesian statistics. This volume provides a thorough account of key basic concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development, which provides, in particular, a detailed treatment of the problem of specification of so-called "prior ignorance". The work is written from the authors' committed Bayesian perspective, but an overview of non-Bayesian theories is provided, and each chapter contains a wide-ranging critical re-examination of controversial issues. The level of mathematics used is such that most material should be accessible to readers with a knowledge of advanced calculus. In particular, no knowledge of abstract measure theory is assumed, and the emphasis throughout is on statistical concepts rather than rigorous mathematics. The book will be an ideal source for all students and researchers in statistics, mathematics, decision analysis, economic and business studies, and all branches of science and engineering, who wish to further their understanding of Bayesian statistics.
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Editorial Reviews

Booknews
Volume one of a series of three volumes (to be followed by Bayesian Computation and Bayesian Methods) provides a thorough account of basic concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development which provides, in particular, a detailed treatment of the problem of specification of so-called "prior ignorance." An overview of non-Bayesian theories is also provided, and each chapter contains a wide-ranging critical re-examination of controversial issues. Annotation c. Book News, Inc., Portland, OR (booknews.com)
From the Publisher
"an excellent primary source for those who wish to learn about the learning and decision process in a situation of uncertainty..." (Measurement Science Technology, February 2001)

"an ideal source for all students and researchers in statistics mathematics, decision analysis, economic and business studies and all branches of science and engineering who wish to further their understanding of Bayesian statistics." (Zentralblatt Fur Didaktik der Mathematik)

"...Bayesians will find it indispensable: non-Bayesians will find, and enjoy, much thought-provoking material to challenge their orthodoxy...." (The Statistician, Vol.51, No.2, 2002)

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Product Details

Meet the Author

About the Authors Jose M. Bernardo received his PhD from University College London and has subsequently been at the University of Valencia, Spain, where he is currently Professor of Statistics and special scientific advisor to the Governor of the State of Valencia. Adrian F. M. Smith received his PhD from University College London and is currently at Imperial College London, where he is Professor of Statistics and Head of the Department of Mathematics

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Table of Contents

1 Introduction 1
2 Foundations 13
3 Generalisations 105
4 Modelling 165
5 Inference 241
6 Remodelling 377
A. Summary of Basic Formulae 427
B. Non-Bayesian Theories 443
References 489
Subject Index 555
Author Index 573
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Customer Reviews

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  • Anonymous

    Posted July 2, 2000

    a nice book hampered by its outrageous price

    This is a good book in bayesian theory. One thing I couldn't comprehend is the price of this book. While bayesians are preaching for the due exposure of the bayesian perspective in the graduate programs of statistics, you write a good book and charge $200 dollars to scare away graduate students, i.e., future statisticians. Unless a paperback version of this book with reasonable price affordable to the students is published, the influence of this book will be very limited.

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