The statistical analysis of extreme data is important for disciplines such as hydrology, insurance, finance, engineering and environmental sciences. This book provides an introduction to the parametric modelling, exploratory analysis and statistical interference for extreme values. Besides numerous data-based examples, the book contains chapters on flood frequency analysis, insurance and finance. This second extended edition include: the statistical modelling of tails in conjunction with the global modelling of distributions with special emphasis on heavy-tailed distribution; the Bayesian methodology with applications to regional flood frequency analysis and credibility estimation in reinsurance business; a thorough treatment of the phenomenon of penultimate distributions; an extension of the chapter about multivariate extreme value models, especially for the Gumbel-McFadden model with an application to the theory of economic choice behaviour; sections about corrosion analysis and oldest-old problem; and risk assessment of financial assets and portfolios in the presence of fat and heavy-tailed distributions by means of the value-at-risk (VaR).
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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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