Strong laws for weighted sums of widely orthant dependent random variables and applications

被引：0
|
作者：
Zhu, Yong [1 ]
Wang, Wei [1 ]
Chen, Kan [2 ]
机构：
[1] Chizhou Univ, Sch Big Data & Artificial Intelligence, Chizhou 247000, Peoples R China
[2] Chaohu Univ, Sch Math & Stat, Chaohu 238024, Peoples R China
来源：
OPEN MATHEMATICS | 2024年 / 22卷 / 01期
关键词：
strong law of large numbers; weighted sums; widely orthant dependent; strong consistency; FIXED-DESIGN REGRESSION; STRONG CONSISTENCY; ASYMPTOTIC UNBIASEDNESS; CONVERGENCE; ESTIMATOR; MODEL;
D O I：
10.1515/math-2024-0027
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
In this study, the strong law of large numbers and the convergence rate for weighted sums of non-identically distributed widely orthant dependent random variables are established. As applications, the strong consistency for weighted estimator in nonparametric regression model and the rate of strong consistency for least-squares estimator in multiple linear regression model are obtained. Some numerical simulations are also provided to verify the validity of the theoretical results.
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页数：14
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