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Estimation of the functional Weibull tail-coefficient

Stéphane Girard 1 Laurent Gardes 2
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
2 IRMA - Institut de Recherche Mathématique Avancée
Abstract : We present a nonparametric family of estimators for the tail coefficient of a Weibull tail-distribution when a functional covariate is available. Our estimators are based on a kernel estimator of extreme conditional quantiles, extending a previous work to the infinite dimensional case. Asymptotic normality of the estimators is proved under mild regularity conditions. Their finite sample performances are illustrated both on simulated and real data.
Keywords : Conditional Weibull tail-coefficient Extreme quantiles Nonparametric estimation
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01571990
Contributor : Stephane Girard <>
Submitted on : Friday, August 4, 2017 - 11:16:52 AM
Last modification on : Tuesday, February 9, 2021 - 3:20:16 PM

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  • HAL Id : hal-01571990, version 1

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Stéphane Girard, Laurent Gardes. Estimation of the functional Weibull tail-coefficient. 10th International Conference on Extreme Value Analysis, Jun 2017, Delft, Netherlands. ⟨hal-01571990⟩

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