Complete and complete moment convergence for weighted sums of arrays of rowwise negatively dependent random variables under the sub-linear expectations

被引：11
|
作者：
Feng, Fengxiang [1 ,2 ]
Wang, Dingcheng [1 ]
Wu, Qunying [2 ]
Huang, Haiwu [3 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China
[2] Guilin Univ Technol, Coll Sci, Guilin, Guangxi, Peoples R China
[3] Hengyang Normal Univ, Coll Math & Stat, Hengyang, Hunan, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2021年 / 50卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Complete convergence; complete moment convergence; sub-linear expectations; negatively dependent random variables; LARGE NUMBERS; STRONG LAW; PROBABILITIES; INEQUALITIES; MODEL;
D O I：
10.1080/03610926.2019.1639747
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, we study complete and complete moment convergence theorems for arrays of rowwise negatively dependent random variables under the sub-linear expectations. The complete and complete moment convergence theorems in the sense of non-additive capacities are established for arrays of rowwise negatively dependent random variables. Our result improves the corresponding result of Wang et al. relative to the classical probability space.
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页码：594 / 608
页数：15
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