Estimating the conditional tail index with an integrated conditional log-quantile estimator in the random covariate case - Archive ouverte HAL
Pré-Publication, Document De Travail Année : 2014

Estimating the conditional tail index with an integrated conditional log-quantile estimator in the random covariate case

Résumé

It is well known that the tail behavior of a heavy-tailed distribution is controlled by a parameter called the tail index. Such a parameter is therefore of primary interest in extreme value analysis, particularly to estimate extreme quantiles. In various applications, the random variable of interest can be linked to a finite-dimensional random covariate. In such a situation, the tail index is function of the covariate and is referred to as the conditional tail index. The goal of this paper is to provide a class of estimators of this quantity. The pointwise weak consistency and asymptotic normality of these estimators are established. We illustrate the finite sample performance of our technique on a simulation study and on a real hurricane data set.
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Dates et versions

hal-01074694 , version 1 (15-10-2014)

Identifiants

  • HAL Id : hal-01074694 , version 1

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Laurent Gardes, Gilles Stupfler. Estimating the conditional tail index with an integrated conditional log-quantile estimator in the random covariate case. 2014. ⟨hal-01074694⟩
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