删失数据中删失指标随机缺失下回归函数的非参数估计(英文)  

Nonparametric Regression Estimation with Missing Censoring Indicators

作　　者：王景乐[1] 郑明[2] 

机构地区：[1]对外经济贸易大学统计学院,北京100029 [2]复旦大学管理学院统计学系,上海200433

出　　处：《应用概率统计》2014年第5期476-490,共15页Chinese Journal of Applied Probability and Statistics

基　　金：supported by the National Natural Science Foundation of China(11271081);2013 Young Teachers Scientific Research Project of University of International Business and Economics(12QD12)

摘　　要：本文在删失数据中删失指标随机缺失的情况下,运用非参数方法给出了回归函数的两种估计量,给出了估计量的一致收敛速度以及渐近分布,并进一步通过数值模拟验证了所提方法在有限样本下的性质.Nonparametric regression estimation has been studied intensively for the censored data. However, in some practical applications, some censoring indicators may be missing because of various reasons. In this paper, we propose two kernel estimators for the regression function when the censoring indicator is missing at random. The strong uniform convergence rates and the asymptotic normality of the estimators are established. Some simulations are carried out to assess the finite sample performances of the proposed methods.

关 键 词：核估计 随机删失 随机缺失 回归函数 

分 类 号：O212.7[理学—概率论与数理统计]