Stationary Bootstrap for U-Statistics under Strong Mixing

被引：2

作者：

Hwang, Eunju ^{[1
]}

Shin, Dong Wan ^{[2
]}

机构：

[1] Gachon Univ, Dept Appl Stat, Seongnam, South Korea

[2] Ewha Womans Univ, Dept Stat, Seoul 120750, South Korea

来源：

COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS | 2015年 / 22卷 / 01期

基金：

新加坡国家研究基金会;

关键词：

Stationary bootstrap; U-statistic; strong mixing; strong consistency; weak consistency; Monte Carlo study;

D O I：

10.5351/CSAM.2015.22.1.081

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：

Validity of the stationary bootstrap of Politis and Romano (1994) is proved for U-statistics under strong mixing. Weak and strong consistencies are established for the stationary bootstrap of U-statistics. The theory is applied to a symmetry test which is a U-statistic regarding a kernel density estimator. The theory enables the bootstrap confidence intervals of the means of the U-statistics. A Monte-Carlo experiment for bootstrap confidence intervals confirms the asymptotic theory.

引用

页码：81 / 93

页数：13

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