Kaplan–Meier estimator and hazard estimator for censored negatively superadditive dependent data. Issue 2 (3rd March 2016) - Shen, Aiting; Wang, Xinghui
Abstract : 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.