An extreme quantile estimator for the log-generalized Weibull-tail model

Abstract : We propose a new estimator for extreme quantiles under the log-generalized Weibull-tail model, introduced by Cees de Valk. This model relies on a new regular variation condition which, in some situations, permits to extrapolate further into the tails than the classical assumption in extreme-value theory. The asymptotic normality of the estimator is established and its finite sample properties are illustrated both on simulated and real datasets.
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Pré-publication, Document de travail
2018
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https://hal.inria.fr/hal-01783929
Contributeur : Stephane Girard <>
Soumis le : vendredi 21 septembre 2018 - 09:42:09
Dernière modification le : dimanche 23 septembre 2018 - 16:35:40

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estimation-erv6.pdf
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  • HAL Id : hal-01783929, version 3

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Clément Albert, Anne Dutfoy, Laurent Gardes, Stéphane Girard. An extreme quantile estimator for the log-generalized Weibull-tail model. 2018. 〈hal-01783929v3〉

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