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.
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页码：5866 / 5882
页数：17
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