Extreme Value Distributions
Published on 10. October 2000
Book
Hardback
196 pages
978-1-86094-224-2 (ISBN)
Description
This important book provides an up-to-date comprehensive and down-to-earth survey of the theory and practice of extreme value distributions - one of the most prominent success stories of modern applied probability and statistics. Originated by E J Gumbel in the early forties as a tool for predicting floods, extreme value distributions evolved during the last 50 years into a coherent theory with applications in practically all fields of human endeavor where maximal or minimal values (the so-called extremes) are of relevance. The book is of usefulness both for a beginner with a limited probabilistic background and to expert in the field.
Reviews / Votes
"... this is a solid mathematical treatment of some topics of extreme value theory addressed to professionals in the field of statistical distributions and statistical inference as well as to people interested in the applications of extreme value distributions. The book can be used very constructively as a textbook or a reference book." Mathematics Abstracts "Extreme Value Distributions is a well-organized, workmanlike treatment of the subject ... Researchers who need to deal with extreme value problems but are novice statisticians will greatly appreciate the clarity of presentation in this book and will wish to obtain copy." The Statisticians, Royal Society of Statistics "The wealth of material and the critical comments by the authors on the various problems considered in the monograph should make it a valuable resource even for a specialist." Mathematical ReviewsMore details
Language
English
Place of publication
London
United Kingdom
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 15 mm
Weight
443 gr
ISBN-13
978-1-86094-224-2 (9781860942242)
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Schweitzer Classification
Persons
Content
Univariate extreme value distributions; generalized extreme value distributions; multivariate extreme value distributions.