Complete f-moment convergence for maximal randomly weighted sums of arrays of rowwise widely orthant dependent random variables and its statistical applications

被引：2

作者：

Wang, Miaomiao ^{[1
]}

Zheng, Shunping ^{[1
]}

Chen, Xi ^{[1
]}

Wang, Xuejun ^{[1
]}

机构：

[1] Anhui Univ, Sch Big Data & Stat, Hefei 230601, Peoples R China

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2024年 / 439卷

关键词：

WOD random variables; Complete moment convergence; Completef-moment convergence; Randomly weighted sums; Complete consistency; LS ESTIMATOR; STRONG LAWS; CONSISTENCY; MODELS;

D O I：

10.1016/j.cam.2023.115596

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we study the complete f-moment convergence for maximal randomly weighted sums of arrays of rowwise widely orthant dependent random variables under some general conditions. The results obtained in the paper extend and improve some previous known ones. As applications of our main results, we not only present convergence for the state observers of linear-time-invariant systems but also obtain complete consistency for the estimators of errors-in-variables regression models based on widely orthant dependent errors. We further perform a numerical simulation to verify the validity of the theoretical results.(c) 2023 Elsevier B.V. All rights reserved.

引用

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