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Convergence of the tail probability for weighted sums of negatively orthant dependent random variables

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成果类型:
期刊论文
作者:
Huang, Haiwu*;Li, Linyan;Lu, Xuewen
通讯作者:
Huang, Haiwu
作者机构:
[Li, Linyan; Huang, Haiwu] Hengyang Normal Univ, Coll Math & Stat, Hengyang 421002, Peoples R China.
[Huang, Haiwu] Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang 421002, Peoples R China.
[Lu, Xuewen] Univ Calgary, Dept Math & Stat, Calgary, AB T2N 1N4, Canada.
通讯机构:
[Huang, Haiwu] H
Hengyang Normal Univ, Coll Math & Stat, Hengyang 421002, Peoples R China.
Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang 421002, Peoples R China.
语种:
英文
关键词:
negatively orthant dependent random variables;the tail probability;strong convergence
期刊:
KYBERNETIKA
ISSN:
0023-5954
年:
2020
卷:
56
期:
4
页码:
646-661
基金类别:
The authors are most grateful to the Editor and the anonymous referees for carefully reading the paper and for offering valuable suggestions, which greatly improved this paper. This paper is supported by the National Nature Science Foundation of China (71963008), the Science and Technology Plan Project of Hunan Province (2016TP1020), Application-Oriented Characterized Disciplines, Double First-Class University Project of Hunan Province (Xiangjiaotong [2018]469), the Scientific Research Fund of Hunan Provincial Education Department (18C0660), the National Statistical Science Research Project of China (2018LY05), the Guangxi Provincial Natural Science Foundation of China (2018GXNSFAA294131) and the Discovery Grants (RGPIN-2018-06466) from Natural Sciences and Engineering Research Council of Canada.
机构署名:
本校为第一且通讯机构
院系归属:
数学与统计学院
摘要:
In this research, strong convergence properties of the tail probability for weighted sums of negatively orthant dependent random variables are discussed. Some sharp theorems for weighted sums of arrays of rowwise negatively orthant dependent random variables are established. These results not only extend the corresponding ones of Cai [4], Wang et al. [19] and Shen [13], but also improve them, respectively. © 2020 Institute of Information Theory and Autom...

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