Overview
- Includes the statistical MS Windows application Academic Xtremes 4.1 and StatPascal on a CD
- Within the applied parts of the book one will find new chapters about Environmental Sciences (co-authored by R.W. Katz) and Conditional Approaches to Financial Data
- The present book is a valuable contribution to the various theoretical and applied problems in the area of extreme value theory...a pleasure to read." (Statistics and Decisions, review of the 2nd ed.)
- This book is complemented by an excellent statistical package on CD ROM... The book is however much more than a manual for the program and it would provide an excellent introduction to the subject for any statistician looking for a practical introduction to the subject of extreme values." (J. Time Series Analysis, review of the 2nd ed.)
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Table of contents (16 chapters)
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Front Matter
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Modeling and Data Analysis
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Front Matter
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Statistical Inference in Parametric Models
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Front Matter
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Elements of Multivariate Statistical Analysis
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Front Matter
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Topics in Insurance, Finance and Hydrology
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Front Matter
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Case Studies in Extreme Value Analysis
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Front Matter
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Keywords
About this book
The statistical analysis of extreme data is important for various disciplines, including hydrology, insurance, finance, engineering and environmental sciences. This book provides a self-contained introduction to the parametric modeling, exploratory analysis and statistical interference for extreme values.
The entire text of this third edition has been thoroughly updated and rearranged to meet the new requirements. Additional sections and chapters, elaborated on more than 100 pages, are particularly concerned with topics like dependencies, the conditional analysis and the multivariate modeling of extreme data. Parts I–III about the basic extreme value methodology remain unchanged to some larger extent, yet notable are, e.g., the new sections about "An Overview of Reduced-Bias Estimation" (co-authored by M.I. Gomes), "The Spectral Decomposition Methodology", and "About Tail Independence" (co-authored by M. Frick), and the new chapter about "Extreme Value Statistics of Dependent Random Variables" (co-authored by H. Drees). Other new topics, e.g., a chapter about "Environmental Sciences", (co--authored by R.W. Katz), are collected within Parts IV–VI.
Reviews
"The book is well written. It assumes a knowledge of statistics, but many of the ideas and techniques can be used by a nonstatistician. As a handbook for XTREMES, it is excellent, and I recommend it highly."
-Computing Reviews
"The present book is a valuable contribution to the various theoretical and applied problems in the area of extreme value theory...a pleasure to read."
-Statistics & Decisions
"This book is complemented by an excellent statistical package on CD ROM... The book is however much more than a manual for the program and it would provide an excellent introduction to the subject for any statistician looking for a practical introduction to the subject of extreme values."
- J. Time Series Analysis
"With general statistics software, appropriate tools for the analysis of real extreme value problems are rarely provided. XTREMES excellently fills this gap in the statistics software market."
-Computational Statistics
"For a practitioner from industry, insurance, or finance who is less concerned with understanding the underlying probability and more interested in applications, this new book will be a good buy."
-JASA
"The book can be highly recommended to all who deal with statistics of extremes." - Zeitschrift fur Mathematik
Authors and Affiliations
Bibliographic Information
Book Title: Statistical Analysis of Extreme Values
Book Subtitle: from Insurance, Finance, Hydrology and Other Fields
Authors: Rolf-Dieter Reiss, Michael Thomas
DOI: https://doi.org/10.1007/978-3-0348-6336-0
Publisher: Birkhäuser Basel
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eBook Packages: Springer Book Archive
Copyright Information: Springer Basel AG 1997
eBook ISBN: 978-3-0348-6336-0Published: 14 October 2013
Edition Number: 1
Number of Pages: XVII, 316
Number of Illustrations: 107 b/w illustrations
Topics: Statistical Theory and Methods, Probability Theory and Stochastic Processes