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Estimation non-paramétrique des quantiles extrêmes conditionnels

Laurent Gardes 1 Stéphane Girard 1 Alexandre Lekina 1 
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 propose a method to estimate quantiles from heavy-tailed distributions when covariate information is available and in the case where the order of the quantile converges to one as the sample size increases. Asymptotic distribution of such an estimator is established in the case where the quantile is in the range of data or near and even beyond the sample. An illustration on simulated data is provided.
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Submitted on : Friday, May 22, 2009 - 9:03:01 AM
Last modification on : Thursday, January 20, 2022 - 5:30:22 PM
Long-term archiving on: : Thursday, June 10, 2010 - 7:34:33 PM


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  • HAL Id : inria-00386572, version 1



Laurent Gardes, Stéphane Girard, Alexandre Lekina. Estimation non-paramétrique des quantiles extrêmes conditionnels. 41èmes Journées de Statistique, SFdS, May 2009, Bordeaux, France. ⟨inria-00386572⟩



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