Statistical analysis of extreme data is vital to many disciplines including hydrology, insurance, finance, engineering and environmental sciences. This book provides a self-contained introduction to parametric modeling, exploratory analysis and statistical interference for extreme values. For this Third Edition, the entire text has been thoroughly updated and rearranged to meet contemporary requirements, with new sections and chapters address such topics as dependencies, the conditional analysis and the multivariate modeling of extreme data. New chapters include An Overview of Reduced-Bias Estimation; The Spectral Decomposition Methodology; About Tail Independence; and Extreme Value Statistics of Dependent Random Variables.
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Editorial Reviews
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"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 "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
From the Back Cover
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.
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Most Helpful Customer Reviews
2 of 4 people found the following review helpful:
3.0 out of 5 stars
Lack of practical insight,
By
This review is from: Statistical Analysis of Extreme Values: From Insurance, Finance, Hydrology and Other Fields (Paperback)
Although the treatment of many extreme values distributions is rather complete at a theoretical point of view, very few practical considerations with respect to the actual way one should use these various EV models is provided. Unless you already know which class of EV distribution to use in your case, this book will not serve much. An overly important aspect of fitting distributions concerns the family of distribution to use for fitting a particular data, and here i haven't found much insight about practical considerations in this book. This is an important gap in this book because it is due to be practical.On the other hand, the estimation of particular EV distributions is thoroughly covered, with theoretical (many references) and practical issues (for the estimation only) well described in every section. Another negative point concerns the distribution of XTREMES provided with the book which is far from complete, and with bugs (changing on-line the values of the parameters of some distributions makes it crash...). I consider this book as a theoretically extended version of the manual of XTREMES, but not a self-sontained statistical book. In summary, if you are interested in a very specific EV family, then this book can be useful, but not as a textbook. Rather go to Castillo (EV in engineering) for a good textbook on EV distributions.
0 of 3 people found the following review helpful:
3.0 out of 5 stars
Unexpected charge,
This review is from: Statistical Analysis of Extreme Values: with Applications to Insurance, Finance, Hydrology and Other Fields (Paperback)
The product is fine and it arrived a week ago, as desired. I bought two other products con amazon.com last year and they were sent to me from U.S. This time the package was sent from New Zealand and that cost me 7.70 of unexpected duties.
1 of 5 people found the following review helpful:
5.0 out of 5 stars
Brilliant book!,
This review is from: Statistical Analysis of Extreme Values: From Insurance, Finance, Hydrology and Other Fields (Paperback)
Especially it is very interesting and advantageous in parts of EVT applicacation in Insurance and Finance!
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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extreme returns, parametric modeling, asset prices, generalized jackknife, parametric inference, testing extreme value conditions, time series approach, tail indices, extreme value distributions, exceedance dfs, beta dfs, limiting dfs, retentation level, first exceedance time, conditional dfs, random scale parameter, upper ordered values, predictive dfs, spherical random vector, fire claim data, tail independence, reciprocal mean cluster sizes, reciprocal hazard function, mean claim size, exceedance process Key Phrases - Capitalized Phrases (CAPs): (learn more)
Continuation of Example, Generalized Pareto Models, The Impact of Large Claims, Advanced Statistical Analysis, Diagnostic Tools, New York, Statistics of Dependent Variables, Poors Index, Water Resour, Conditional Extremal Analysis, Environmental Sciences, Actuarial Decisions, Predicting the Serial Conditional, Segmentation According, Generalized Pareto Distributions, Academic Press, Estimation of the Net Premium, Monte Carlo, Models of Time Series, Visualization of Data, Maximum Likelihood Estimation, Fort Collins, Multivariate Peaks Over Threshold, Annual Wind-Speed Maxima, Empirical Evidence Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Surprise Me!
extreme returns, parametric modeling, asset prices, generalized jackknife, parametric inference, testing extreme value conditions, time series approach, tail indices, extreme value distributions, exceedance dfs, beta dfs, limiting dfs, retentation level, first exceedance time, conditional dfs, random scale parameter, upper ordered values, predictive dfs, spherical random vector, fire claim data, tail independence, reciprocal mean cluster sizes, reciprocal hazard function, mean claim size, exceedance process Key Phrases - Capitalized Phrases (CAPs): (learn more)
Continuation of Example, Generalized Pareto Models, The Impact of Large Claims, Advanced Statistical Analysis, Diagnostic Tools, New York, Statistics of Dependent Variables, Poors Index, Water Resour, Conditional Extremal Analysis, Environmental Sciences, Actuarial Decisions, Predicting the Serial Conditional, Segmentation According, Generalized Pareto Distributions, Academic Press, Estimation of the Net Premium, Monte Carlo, Models of Time Series, Visualization of Data, Maximum Likelihood Estimation, Fort Collins, Multivariate Peaks Over Threshold, Annual Wind-Speed Maxima, Empirical Evidence Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Surprise Me!
Citations (learn more)
2
books
cite this book:
- Levy Processes by Ole Eiler Barndorff-Nielsen in Back Matter
- Empirical Process Techniques for Dependent Data by Herold Dehling in Back Matter
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