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2000
The extreme (upper or lower) parts of a sample, such as flood discharges; high concentration of air pollutants; claim sizes over a higher priority in reinsurance business; larger losses on financial markets; have exhibited an increasing risk potential during the last decades.
Rolf-Dieter Reiss, Michael Thomas
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The extreme (upper or lower) parts of a sample, such as flood discharges; high concentration of air pollutants; claim sizes over a higher priority in reinsurance business; larger losses on financial markets; have exhibited an increasing risk potential during the last decades.
Rolf-Dieter Reiss, Michael Thomas
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Extreme Value Analysis for Financial Risk Management
Annual Review of Statistics and Its Application, 2021This article reviews methods from extreme value analysis with applications to risk assessment in finance. It covers three main methodological paradigms: the classical framework for independent and identically distributed data with application to risk estimation for market and operational loss data, the multivariate framework for cross-sectional ...
Nolde, N, Zhou, Chen
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Regional Extreme Value Analysis
2021This chapter focuses on the occurrence of extreme natural hazards in non-instrumented locations, whose neighborhood contains sites for which measured data are available. The spatial regionalization approach developed here, which is based on the detection of regions that are homogeneous in terms of risk, allows to propose a localized quantification of ...
Jérôme Weiss, Marc Andreewsky
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IT Design for Resiliency Using Extreme Value Analysis
2021Safety-critical systems are designed to operate millions of hours without losing or harming life. Millions of hours enable events with small occurrence probability to materialise. Owing to this, rare events have to be factored when designing for millions of safe operating hours.
Szilárd Bozóki, András Pataricza
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Problems in the extreme value analysis
Structural Safety, 2008Engineering design for structural safety is largely based on the statistics of natural hazards. These statistics are utilized by applying the theory of extremes, which predicts a cumulative distribution function of the extreme events. The parameters of this distribution are found by a fit to the historical extremes and the probabilities of potentially ...
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Application of extreme value analysis to Weibull data
Quarterly Journal of the Royal Meteorological Society, 1983AbstractIn the application of extreme value analysis it is usually assumed that the size of the samples from which the extreme values are obtained is sufficiently large for the asymptotic extreme value distribution to be used. The necessary sample size depends upon the population distribution and this is generally not known; but assuming a Weibull ...
DJT CARTER, PG CHALLENOR
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Trend Analysis of Extreme Values
2011In Dierckx and Teugels (Environmetrics 2:1–26) we concentrated on testing whether an instantaneous change occurs in the value of the extreme value index. This short article illustrates with an explicit example that in some cases the extreme value index seems to change gradually rather than instantaneously.
Goedele Dierckx, Jef Teugels
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Bayesian analysis of extreme value regression
Applied Economics Letters, 2012The article takes up Bayesian inference in extreme value distributions and also considers extreme value regression, which appears relatively uncommon in the regression literature. Numerical methods are organized around Gibbs sampling. It is shown that simple and reliable numerical techniques can be devised by exploiting the particular form of the ...
Emmanuel N. Papadakis +1 more
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Extreme-value Analysis Of Oscillations.
1957PhD ; Mechanics ; University of Michigan, Horace H. Rackham School of Graduate Studies ; http://deepblue.lib.umich.edu/bitstream/2027.42/181936/2/5801380 ...
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