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Un nouvel estimateur des quantiles extrêmes basé sur le modèle “log Weibull-tail” généralisé

Clément Albert 1 Anne Dutfoy 2 Laurent Gardes 3 Stéphane Girard 1
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann
Abstract : Extreme quantile estimation remains a major statistical challenge. In this communication, the problem is addressed in the framework of the so-called "log-Generalized Weibull tail limit", where the logarithm of the inverse cumulative hazard rate function is supposed to be of extended regular variation. Based on this model, a new estimator of extreme quantiles is proposed. Its asymptotic normality is established and its behavior in practice is illustrated on simulated data.
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Submitted on : Tuesday, June 5, 2018 - 9:02:12 AM
Last modification on : Wednesday, November 3, 2021 - 6:02:05 AM
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  • HAL Id : hal-01807672, version 1



Clément Albert, Anne Dutfoy, Laurent Gardes, Stéphane Girard. Un nouvel estimateur des quantiles extrêmes basé sur le modèle “log Weibull-tail” généralisé. SFDS 2018 - 50èmes Journées de Statistique, May 2018, Saclay, France. pp.1-6. ⟨hal-01807672⟩



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