HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

Functional nonparametric estimation of conditional extreme quantiles

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 address the estimation of quantiles from heavy-tailed distributions when functional covariate information is available and in the case where the order of the quantile converges to one as the sample size increases. Such "extreme" quantiles can be located in the range of the data or near and even beyond the boundary of the sample, depending on the convergence rate of their order to one. Nonparametric estimators of these functional extreme quantiles are introduced, their asymptotic distributions are established and their finite sample behavior is investigated.
Complete list of metadata

Cited literature [28 references]  Display  Hide  Download

Contributor : Laurent Gardes Connect in order to contact the contributor
Submitted on : Thursday, April 25, 2013 - 11:46:12 AM
Last modification on : Thursday, January 20, 2022 - 5:28:06 PM
Long-term archiving on: : Monday, April 3, 2017 - 9:36:48 AM


Files produced by the author(s)




Laurent Gardes, Stéphane Girard, Alexandre Lekina. Functional nonparametric estimation of conditional extreme quantiles. Journal of Multivariate Analysis, Elsevier, 2010, 101 (2), pp.419-433. ⟨10.1016/j.jmva.2009.06.007⟩. ⟨hal-00289996v4⟩



Record views


Files downloads