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Extreme Value and Related Models With Applications in Engineering and Science

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Extreme Value and Related Models With Applications in Engineering and Science Synopsis

A straightforward, practical guide to extreme value modeling for today's world

Measuring and interpreting data for extreme values presents a unique and important challenge that has far-reaching implications for all aspects of modern engineering and science. Extreme Value and Related Models with Applications in Engineering and Science reflects the latest information in this growing field. The book incorporates illuminating real-world examples from such areas as structural engineering, hydraulics, meteorology, materials science, highway traffic analysis, environmetrics, and climatology, and is designed to help engineers, mathematicians, statisticians, and scientists gain a clearer understanding of extreme value theory and then translate that knowledge into practical applications within their own fields of research.

The book provides:

  • A unique focus on modern topics including data analysis and inference
  • Specific data in such areas as wind, flood, chain strength, electrical insulation, fatigue, precipitation, and wave heights
  • Useful techniques for addressing extreme value problems, including discrete, continuous, univariate, and multivariate models
  • Coverage of order statistics, return period, exceedances and shortfalls, along with detailed explanations on how to obtain exact distributions for these statistics
  • An in-depth look at asymptotic models and the limit distributions of maxima, minima, and other order statistics

Enhanced with numerous graphs and exercises, plus an extensive bibliography for further study, this text is an important reference source for engineers designing structures that will withstand even the most extreme circumstances.

About This Edition

ISBN: 9780471671725
Publication date:
Author: Enrique Castillo
Publisher: Wiley-Interscience an imprint of Wiley
Format: Hardback
Pagination: 362 pages
Series: Wiley Series in Probability and Statistics
Genres: Mathematics