Asymptotic normality of convergent estimates of conditional quantiles

被引：33

作者：

Berlinet, A ^{[1
]}

Gannoun, A ^{[1
]}

Matzner-Lober, E ^{[1
]}

机构：

[1] Univ Montpellier 2, Dept Math Sci, F-34095 Montpellier 5, France

来源：

STATISTICS | 2001年 / 35卷 / 02期

关键词：

asymptotic normality; conditional quantiles; alpha-mixing stationary processes; time series; forecasting;

D O I：

10.1080/02331880108802728

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 state sufficient conditions for asymptotic normality of convergent estimates of conditional quantiles, irrespective of data dependence and consider the particular case of cu-mixing stationary processes under optimal condition of convergence. We apply this result to confidence intervals building for time series predictors based on nonparametric estimates of the conditional median.

引用

页码：139 / 169

页数：31

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