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

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research 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

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.