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More About This Textbook
Overview
This book provides readers with an elementary and comprehensive discussion on extreme value and related models. By using a large number of practical data from different science and engineering disciplines, it illustrates the practical importance and usefulness of extreme value modeling. Unusual, provocative, and concrete examples are derived from areas such as ocean engineering, structural engineering, hydraulics, meteorology, materials science, fatigue studies, electrical strength of materials, highway traffic analysis, corrosion science, environmetrics, climatology, among others.
Editorial Reviews
From the Publisher
“This text provides an extensive coverage of the distribution theory of extreme values…the text is well presented with clearly displayed equations and diagrams…a particularly useful reference book…” (International Statistical Institute, Vol 25 (2) August 2005)Product Details
Related Subjects
Meet the Author
ENRIQUE CASTILLO, PhD, is a Professor of Applied Mathematics at theUniversity of Cantabria in Santander, Spain. He is a mathematicianand a civil engineer and member of the Spanish Royal Academy ofEngineering.
ALI S. HADI, PhD, is a Professor of Mathematical, Statistical,and Computational Sciences at the American University in Cairo,Egypt. He is a Stephen H. Weiss Presidential Fellow and ProfessorEmeritus at Cornell University.
N. BALAKRISHNAN, PhD, is a Professor in the Department ofMathematics and Statistics at McMaster University in Ontario,Canada. He is a Fellow of the American Statistical Association andcurrently the Editor-in-Chief of Communications in Statistics andWiley's Encyclopedia of Statistical Sciences, Second Edition.
JOSÉ M. SARABIA, PhD, is a Professor of Statistics in theDepartment of Economics at the University of Cantabria, Spain. Heis a member of the American Statistical Association and isAssociate Editor of the journal Test.
Table of Contents
Preface.
I: DATA, INTRODUCTION AND MOTIVATION.
1. Introduction and Motivation.
II: PROBABILISTIC MODELS USEFUL IN EXTREMES.
2. Discrete Probabilistic Models.
3. Continuous Probabilistic Models.
III: MODEL ESTIMATION, SELECTION, AND VALIDATION.
4. Model Estimation.
5. Model Selection and Validation.
IV: EXACT MODELS FOR ORDER STATISTICS AND EXTREMES.
6. Order Statistics.
7. Point Processes and Exact Models.
V: ASYMPTOTIC MODELS FOR EXTREMES AND EXCEEDANCES.
8. Limit Distributions of Order Statistics.
9. Limit Distributions of Exceedances.
10. Multivariate Extremes.
Appendix: Statistical Tables.
Bibliography.
Index.