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Conference papers

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, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
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.
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Submitted on : Thursday, March 21, 2013 - 10:36:35 AM
Last modification on : Wednesday, July 1, 2020 - 1:46:04 PM


  • HAL Id : hal-00803119, version 1



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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