Kaplan-Meier estimator and hazard estimator for censored negatively superadditive dependent data

被引:9
|
作者
Shen, Aiting [1 ]
Wang, Xinghui [2 ]
机构
[1] Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China
[2] Anhui Univ, Sch Econ, Hefei 230601, Peoples R China
基金
中国国家自然科学基金;
关键词
Kaplan-Meier estimator; hazard estimator; negatively superadditive dependent random variables; strong convergence rate; PRODUCT-LIMIT ESTIMATOR; RANDOM-VARIABLES; COMPLETE CONVERGENCE; WEIGHTED SUMS; LARGE-SAMPLE; INEQUALITIES;
D O I
10.1080/02331888.2015.1038269
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 strong convergence properties for the Kaplan-Meier estimator and hazard estimator based on censored negatively superadditive dependent data. Under some mild conditions, the strong convergence rate of the Kaplan-Meier estimator and hazard estimator is established. In addition, the strong representation of the Kaplan-Meier estimator and hazard estimator is also obtained with the remainder of order O(n(-1/2) log(1/2) n) a.s. Our results established in the paper generalize the corresponding ones for independent random variables and negatively associated random variables.
引用
收藏
页码:377 / 388
页数:12
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