Bayesian Theory / Edition 1

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Overview

Recent books in the Wiley Series in Probability and Mathematical Statistics Editors Vic Barnett J. Stuart Hunter Adrian F.M. Smith Geoffrey S. Watson Ralph A. Bradley Joseph B. Kadane Stephen M. Stigler Nicholas I. Fisher David G. Kendall Jozef L. Teugels Optimal Design of Experiments Friedrich Pukelsheim, Universität Augsburg, Augsburg, Germany Optimal Design of Experiments presents the first complete theoretical development of optimal design for the linear model, a unified exposition that embraces a wide variety of design problems. It describes the statistical theory involved in designing experiments, and applies it to typical special cases. The design problems originating from statistics are solved using tools from linear algebra and convex analysis. The material is presented in a very clear, careful and organized way. Rather than assaulting traditional ways of thinking about optimal design, this book pulls together formerly separate entities to create a common framework for diverse design problems that share a common goal. Statisticians, mathematicians, engineers, and operations research specialists will find this book stimulating, challenging, and an asset to their work. 1993 Statistics for Spatial Data, Revised Edition Noel Cressie, Iowa State University, USA Designed for the scientific and engineering professional eager to exploit its enormous potential, Statistics for Spatial Data is a primer to the theory as well as the nuts-and-bolts of this influential technique. Focusing on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, and reveals how spatial statistical models can be used to solve a host of problems in science and engineering. The previous edition was hailed by Mathematical Reviews as "an excellent book which…will become a basic reference". Revised to reflect state-of-the-art developments, this edition also features many detailed examples, numerous illustrations, and over 1000 references. The first fully comprehensive introduction, Statistics for Spatial Data is an essential guide for professionals in biology, earth sciences, civil, electrical and agricultural engineering, geography, epidemiology, and ecology. 1993

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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

Foundations.

Generalisations.

Modelling.

Inference.

Remodelling.

Appendices.

References.

Indexes.

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Customer Reviews

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Sort by: Showing 1 Customer Reviews
  • 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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