Functional kernel estimators of conditional extreme quantiles

Stephane Girard 1 Laurent Gardes 2
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We address the estimation of conditional quantiles when the covariate is functional and when the order of the quantiles converges to one as the sample size increases. In a first time, we investigate to what extent these large conditional quantiles can still be estimated through a functional kernel estimator of the conditional survival function. Sufficient conditions on the rate of convergence of their order to one are provided to obtain asymptotically Gaussian distributed estimators. In a second time, basing on these result, a functional Weissman estimator is derived, permitting to estimate large conditional quantiles of arbitrary large order. These results are illustrated on finite sample situations.
Type de document :
Communication dans un congrès
7èmes Journées de Statistique Fonctionnelle et Opératorielle, Jun 2012, Montpellier, France
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https://hal.archives-ouvertes.fr/hal-00803119
Contributeur : Stephane Girard <>
Soumis le : jeudi 21 mars 2013 - 10:36:35
Dernière modification le : mardi 6 mai 2014 - 11:26:38

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  • HAL Id : hal-00803119, version 1

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Stephane Girard, Laurent Gardes. Functional kernel estimators of conditional extreme quantiles. 7èmes Journées de Statistique Fonctionnelle et Opératorielle, Jun 2012, Montpellier, France. 〈hal-00803119〉

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