Complete moment convergence for randomly weighted sums of extended negatively dependent random variables with application to semiparametric regression models

被引：7
|
作者：
Cheng, Nan [1 ]
Lu, Chao [1 ]
Qi, Jibing [2 ]
Wang, Xuejun [1 ]
机构：
[1] Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China
[2] Hefei Normal Univ, Sch Math & Stat, Hefei 230601, Peoples R China
来源：
STATISTICAL PAPERS | 2022年 / 63卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Extended negatively dependent random variables; Complete moment convergence; Randomly weighted sums; Semiparametric regression models; Complete consistency; LAW;
D O I：
10.1007/s00362-021-01244-1
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 paper, we investigate the complete moment convergence for randomly weighted sums of extended negatively dependent (END) random variables. The results obtained in this paper extended the corresponding one of Li et al. (J Inequalities Appl 2017:16, 2017). As an application, we study the complete consistency for the estimator of semiparametric regression models based on END random variables by using the complete convergence that we established. Finally, we have conducted comprehensive simulation studies to demonstrate the validity of obtained theoretical results.
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页码：397 / 419
页数：23
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