Open Access
2013 A moment estimator for the conditional extreme-value index
Gilles Stupfler
Electron. J. Statist. 7: 2298-2343 (2013). DOI: 10.1214/13-EJS846

Abstract

In extreme value theory, the so-called extreme-value index is a parameter that controls the behavior of a distribution function in its right tail. Knowing this parameter is thus essential to solve many problems related to extreme events. In this paper, the estimation of the extreme-value index is considered in the presence of a random covariate, whether the conditional distribution of the variable of interest belongs to the Fréchet, Weibull or Gumbel max-domain of attraction. The pointwise weak consistency and asymptotic normality of the proposed estimator are established. We examine the finite sample performance of our estimator in a simulation study and we illustrate its behavior on a real set of fire insurance data.

Citation

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Gilles Stupfler. "A moment estimator for the conditional extreme-value index." Electron. J. Statist. 7 2298 - 2343, 2013. https://doi.org/10.1214/13-EJS846

Information

Published: 2013
First available in Project Euclid: 19 September 2013

zbMATH: 1293.62081
MathSciNet: MR3108815
Digital Object Identifier: 10.1214/13-EJS846

Subjects:
Primary: 62G05 , 62G20 , 62G30 , 62G32

Keywords: asymptotic normality , consistency , extreme-value index , moment estimator , random covariate

Rights: Copyright © 2013 The Institute of Mathematical Statistics and the Bernoulli Society

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