A note on quantile estimation for long-range dependent stochastic processes

被引：9
|
作者：
Youndjé, É [1 ]
Vieu, P
机构：
[1] Univ Rouen, Lab Raphael Salem, UMR 6085, Mont St Aignan, France
[2] Univ Toulouse 3, Lab Stat & Probabil, F-31062 Toulouse, France
来源：
STATISTICS & PROBABILITY LETTERS | 2006年 / 76卷 / 02期
关键词：
long memory; quantile estimation; kernel estimation; rates of convergence;
D O I：
10.1016/j.spl.2005.06.015
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：
This note investigates the consistency properties of the kernel-type estimator of a quantile, in the setting of a long memory stationary stochastic process. Under a general long-range dependence situation (without any restriction of gaussian type) we give consistency results, and rates of convergence. An interesting by-product of this paper is a new consistency result for kernel-type estimator of a smooth distribution function (with rates) over the whole real line. (C) 2005 Elsevier B.V. All rights reserved.
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页码：109 / 116
页数：8
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