The p-quantile residual life function summarizes the lifetime data in a useful and simple concept and in units of time. For uncensored data or when the upper tail of the observations is not censored, this function can be estimated by applying the well-known Kaplan-Meier survival estimator. But, when research terminates in heavy right-censored lifetime data which is the case of many biomedical and survival studies, the p-quantile residual life function is not estimable in this way. In this paper, we propose a novel semi-parametric estimator of the p-quantile residual life function in such cases. It combines the nonparametric Kaplan-Meier survival estimator with an approximated tail model motivated by the extreme value theory. The proposed estimator has been examined by a simulation study and applied to a lifetime data set in the sequel.

p分位数的剩余寿命函数以有用和简单的概念并以时间单位总结了寿命数据。对于未经审查的数据或未审查观测值的上尾部时，可以通过应用众所周知的Kaplan-Meier生存估计器来估计此功能。但是，当许多生物医学和生存研究的情况下，当研究终止于严格的右删失的寿命数据时，就无法以这种方式估计p分位数的剩余寿命函数。在本文中，我们提出了在这种情况下p分位数剩余寿命函数的新型半参数估计器。它结合了非参数Kaplan-Meier生存估计器和由极值理论驱动的近似尾部模型。拟议的估计量已通过模拟研究进行了检验，并应用于续集中的寿命数据集。