Strong convergence for weighted sums of (α, β)-mixing random variables and application to simple linear EV regression model

被引：0
|
作者：
Hu, Wenjing [1 ]
Wang, Wei [1 ]
Wu, Yi [1 ]
机构：
[1] Chizhou Univ, Ctr Appl Math, Sch Big Data & Artificial Intelligence, Chizhou 247000, Peoples R China
来源：
OPEN MATHEMATICS | 2024年 / 22卷 / 01期
关键词：
(alpha; beta)-mixing random variables; complete convergence; strong law of large numbers; simple linear errors-in-variables model; ASYMPTOTIC PROPERTIES; MOMENT CONVERGENCE; LS ESTIMATORS; CONSISTENCY;
D O I：
10.1515/math-2024-0003
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
In this article, the complete convergence and the Kolmogorov strong law of large numbers for weighted sums of (alpha, beta)-mixing random variables are presented. An application to simple linear errors-in-variables model is provided. Simulation studies are also carried out to support the theoretical results.
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页数：15
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