COMPLETE CONVERGENCE FOR WEIGHTED SUMS OF AANA RANDOM VARIABLES AND ITS APPLICATION IN NONPARAMETRIC REGRESSION MODELS

被引：0

作者：

Shen, Aiting ^{[1
]}

Zhang, Yajing ^{[1
]}

机构：

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

来源：

JOURNAL OF THE KOREAN MATHEMATICAL SOCIETY | 2021年 / 58卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Asymptotically almost negatively associated random variables; strong law of large numbers; complete convergence; nonparametric regression model; complete consistency; DEPENDENT RANDOM-VARIABLES; MULTIPLE-REGRESSION; INEQUALITIES; ARRAYS;

D O I：

10.4134/JKMS.j200029

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we main study the strong law of large numbers and complete convergence for weighted sums of asymptotically almost negatively associated (AANA, in short) random variables, by using the Marcinkiewicz-Zygmund type moment inequality and Roenthal type moment inequality for AANA random variables. As an application, the complete consistency for the weighted linear estimator of nonparametric regression models based on AANA errors is obtained. Finally, some numerical simulations are carried out to verify the validity of our theoretical result.

引用

页码：327 / 349

页数：23

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