Complete moment convergence for weighted sums of weakly dependent random variables and its application in nonparametric regression model

被引：48

作者：

Wu, Yi ^{[1
]}

Wang, Xuejun ^{[1
]}

Hu, Shuhe ^{[1
]}

机构：

[1] Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China

来源：

STATISTICS & PROBABILITY LETTERS | 2017年 / 127卷

基金：

中国国家自然科学基金;

关键词：

Weakly dependent random variables; Complete moment convergence; Complete convergence; Nonparametric regression model; Complete consistency; FIXED-DESIGN REGRESSION; INEQUALITIES; PROBABILITY;

D O I：

10.1016/j.spl.2017.03.027

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：

In this paper, some results on the complete moment convergence for weighted sums of weakly dependent (or p*-mixing) random variables are established. The results obtained in this paper improve and extend the corresponding one of Sung (2010). As an application of the main results, we present a result on complete consistency for the weighted estimator in a nonparametric regression model based on p*-mixing errors. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：56 / 66

页数：11

共 26 条

[1] CONVERGENCE RATES IN LAW OF LARGE NUMBERS [J].