An Introduction to Statistical Modeling of Extreme Values

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Springer Science & Business Media, Aug 20, 2001 - Mathematics - 208 pages
Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.
 

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Contents

Introduction
1
Basics of Statistical Modeling
18
Classical Extreme Value Theory and Models
45
Threshold Models
74
Extremes of Dependent Sequences
92
Extremes of Nonstationary Sequences
105
A Point Process Characterization of Extremes
124
Multivariate Extremes
142
Further Topics
169
A Computational Aspects
185
References
195
Index
205
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