WOD 随机变量加权和的强收敛性及其在 EV 回归模型中的应用

IF 0.6 4区数学 Q4 MATHEMATICS, APPLIED

Applications of Mathematics Pub Date : 2023-12-08 DOI:10.21136/AM.2023.0004-23

Liwang Ding, Caoqing Jiang

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引用次数: 0

摘要

我们研究了广泛正交依存（WOD）随机变量加权和的强收敛性。作为应用，我们进一步研究了 WOD 随机变量 EV 回归模型中最小二乘估计的强一致性。为了证实理论结果，我们进行了模拟研究。

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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Strong convergence for weighted sums of WOD random variables and its application in the EV regression model

The strong convergence for weighted sums of widely orthant dependent (WOD) random variables is investigated. As an application, we further investigate the strong consistency of the least squares estimator in EV regression model for WOD random variables. A simulation study is carried out to confirm the theoretical results.

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来源期刊

Applications of Mathematics 数学-应用数学

CiteScore

1.50

自引率

0.00%

发文量

审稿时长

3.0 months

期刊介绍： Applications of Mathematics publishes original high quality research papers that are directed towards applications of mathematical methods in various branches of science and engineering. The main topics covered include: - Mechanics of Solids; - Fluid Mechanics; - Electrical Engineering; - Solutions of Differential and Integral Equations; - Mathematical Physics; - Optimization; - Probability Mathematical Statistics. The journal is of interest to a wide audience of mathematicians, scientists and engineers concerned with the development of scientific computing, mathematical statistics and applicable mathematics in general.