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.

引用

页码：109 / 116

页数：8

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