右删失数据条件密度函数的非参数估计  

Nonparametric Conditional Density Estimation for Right-Censored Data

作　　者：薛婧 

机构地区：[1]山西财经大学统计学院,山西 太原

出　　处：《统计学与应用》2022年第5期1168-1179,共12页Statistical and Application

摘　　要：本文考虑响应变量受到随机右删失的回归模型,在右删失数据与未受删失影响数据条件独立的情况下,构造了一种右删失数据条件密度函数的非参数估计量,进而得到该估计量的一致强相合性及其收敛速度,最后通过模拟探究了估计量的估计效果。In this paper, we consider a regression model in which the response is subject to random right censored. Under the assumption that survival time and censored time are conditional independent, we construct a nonparametric conditional density estimator. The uniform strong consistency of the conditional density estimator and its convergence rate are derived. Finally, we study the accuracy of the estimator.

关 键 词：右删失数据 非参数估计 条件密度 一致强相合性 

分 类 号：O212.1[理学—概率论与数理统计]