Complete convergence for weighted sums of WNOD random variables and its applications

被引：4

作者：

Ning, Mingming ^{[1
]}

Wu, Caoqing ^{[1
]}

Shen, Aiting ^{[1
]}

机构：

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

来源：

STOCHASTICS-AN INTERNATIONAL JOURNAL OF PROBABILITY AND STOCHASTIC PROCESSES | 2020年 / 92卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Widely negative orthant dependent random variables; complete convergence; nonparametric regression model; complete consistency; DEPENDENT RANDOM-VARIABLES; REGRESSION;

D O I：

10.1080/17442508.2019.1595623

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we mainly studied the complete convergence for weighted sums of widely negative orthant dependent (WNOD, in short) random variables. Some sufficient conditions to prove the complete convergence are provided. As an application, the complete consistency for the weighted estimator of nonparametric regression model is established, and the simulation study is provided to evaluate the finite sample performance of the consistency for the nearest neighbour weight function estimator.

引用

页码：24 / 45

页数：22

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