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

IF 1 4区数学 Q1 MATHEMATICS

Open Mathematics Pub Date : 2024-05-22 DOI:10.1515/math-2024-0003

Wenjing Hu, Wei Wang, Yi Wu

引用次数: 0

Abstract

In this article, the complete convergence and the Kolmogorov strong law of large numbers for weighted sums of

( α , β )

\left(\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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(α, β)混合随机变量加权和的强收敛性及其在简单线性 EV 回归模型中的应用

本文提出了( α , β ) \left(\alpha,\beta)-混合随机变量加权和的完全收敛性和柯尔莫哥洛夫强大数定律。提供了简单线性变量误差模型的应用。还进行了仿真研究以支持理论结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Open Mathematics MATHEMATICS-

CiteScore

2.40

自引率

5.90%

发文量

审稿时长

16 weeks

期刊介绍： Open Mathematics - formerly Central European Journal of Mathematics Open Mathematics is a fully peer-reviewed, open access, electronic journal that publishes significant, original and relevant works in all areas of mathematics. The journal provides the readers with free, instant, and permanent access to all content worldwide; and the authors with extensive promotion of published articles, long-time preservation, language-correction services, no space constraints and immediate publication. Open Mathematics is listed in Thomson Reuters - Current Contents/Physical, Chemical and Earth Sciences. Our standard policy requires each paper to be reviewed by at least two Referees and the peer-review process is single-blind. Aims and Scope The journal aims at presenting high-impact and relevant research on topics across the full span of mathematics. Coverage includes: