Complete convergence and strong law of large numbers for arrays of random variables under sublinear expectations

被引：15

作者：

Lin, Yiwei ^{[1
]}

Feng, Xinwei ^{[1
,2
]}

机构：

[1] Shandong Univ, Sch Math, Jinan, Shandong, Peoples R China

[2] Chinese Univ Hong Kong, Dept Stat, Shatin, Hong Kong, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2020年 / 49卷 / 23期

关键词：

Sublinear expectation; complete convergence; strong law of large numbers; widely negative dependence; array of random variables;

D O I：

10.1080/03610926.2019.1625924

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this article, complete convergence theorems are obtained for arrays of widely negative dependent random variables under sublinear expectations. We improve the corresponding results in probability space, and provide a new method to prove them. As an application, we obtain the strong law of large numbers for arrays of random variables under sublinear expectations.

引用

页码：5866 / 5882

页数：17

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