From the Publisher:
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. Presents a novel discussion of model comparison and choice from a Bayesian perspective. An overview of non-Bayesian theories is provided and each chapter contains a wide-ranging critical re-examination of controversial issues.
From the Back Cover:
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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