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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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Contributor : Stephane Girard <>
Submitted on : Friday, September 21, 2018 - 9:42:09 AM
Last modification on : Thursday, March 26, 2020 - 8:49:33 PM
Document(s) archivé(s) le : Saturday, December 22, 2018 - 1:23:09 PM


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  • HAL Id : hal-01783929, version 3


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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