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Extreme value theory

About: Extreme value theory is a research topic. Over the lifetime, 8063 publications have been published within this topic receiving 196938 citations. The topic is also known as: extreme value analysis & EVA.


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20 Aug 2001
TL;DR: This paper presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually cataloging and modeling extreme value values in sequences.
Abstract: 1. Introduction.- 2. Basics of Statistical Modeling.- 3. Classical Extreme Value Theory and Models.- 4. Threshold Models.- 5. Extremes of Dependent Sequences.- 6. Extremes of Non-Stationary Sequences.- 7. A Point Process Characterization of Extremes.- 8. Multivariate Extremes.- 9. Further Topics.- Appendix A: Computational Aspects.- Index.

4,476 citations

Journal ArticleDOI
TL;DR: In this article, an Introduction to Statistical Modeling of Extreme Values is presented, along with a discussion of statistical models of extreme values and their application in statistical modeling of extreme value.
Abstract: (2002). An Introduction to Statistical Modeling of Extreme Values. Technometrics: Vol. 44, No. 4, pp. 397-397.

3,568 citations

Journal ArticleDOI
TL;DR: In this article, a method for making statistical inferences about the upper tail of a distribution function is presented for estimating the probabilities of future extremely large observations, where the underlying distribution function satisfies a condition which holds for all common continuous distribution functions.
Abstract: A method is presented for making statistical inferences about the upper tail of a distribution function. It is useful for estimating the probabilities of future extremely large observations. The method is applicable if the underlying distribution function satisfies a condition which holds for all common continuous distribution functions.

3,504 citations

Journal ArticleDOI
TL;DR: In this paper, the authors introduce a method for the evaluation of the seismic risk at the site of an engineering project, in terms of a ground motion parameter (such as peak acceleration) versus average return period.
Abstract: This paper introduces a method for the evaluation of the seismic risk at the site of an engineering project. The results are in terms of a ground motion parameter (such as peak acceleration) versus average return period. The method incorporates the influence of all potential sources of earthquakes and the average activity rates assigned to them. Arbitrary geographical relationships between the site and potential point, line, or areal sources can be modeled with computational ease. In the range of interest, the derived distributions of maximum annual ground motions are in the form of Type I or Type II extreme value distributions, if the more commonly assumed magnitude distribution and attenuation laws are used.

3,081 citations

Journal ArticleDOI
TL;DR: In this paper, the statistics Gi(d) and Gi*(d), introduced in Getis and Ord (1992) for the study of local pattern in spatial data, are extended and their properties further explored.
Abstract: The statistics Gi(d) and Gi*(d), introduced in Getis and Ord (1992) for the study of local pattern in spatial data, are extended and their properties further explored. In particular, nonbinary weights are allowed and the statistics are related to Moran's autocorrelation statistic, I. The correlations between nearby values of the statistics are derived and verified by simulation. A Bonferroni criterion is used to approximate significance levels when testing extreme values from the set of statistics. An example of the use of the statistics is given using spatial-temporal data on the AIDS epidemic centering on San Francisco. Results indicate that in recent years the disease is intensifying in the counties surrounding the city.

2,638 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023288
2022541
2021404
2020389
2019399
2018355