Functional nonparametric estimation of conditional extreme quantiles

被引:36
|
作者
Gardes, Laurent [1 ]
Girard, Stephane [1 ]
Lekina, Alexandre [1 ]
机构
[1] INRIA Rhone Alpes & LJK, Team Mistis, F-38334 Montbonnot St Martin, St Ismier, France
关键词
Conditional quantile; Extreme values; Nonparametric estimation; Functional data; MODELS;
D O I
10.1016/j.jmva.2009.06.007
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:419 / 433
页数:15
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