Nonparametric robust regression estimation for censored data

被引:0
|
作者
Mohamed Lemdani
Elias Ould Saïd
机构
[1] Univ. de Lille 2.,Lab. Biomathématiques, Fac. de Pharmacie
[2] Univ. Lille Nord de France,undefined
[3] Univ. du Littoral Côte d’Opale,undefined
[4] LMPA,undefined
来源
Statistical Papers | 2017年 / 58卷
关键词
Asymptotic normality; Censored data; Kaplan-Meier estimator; Kernel estimator; Robust estimation; Uniform almost sure convergence; Primary 62G20; Secondary 62G07; 62N01; 62E20;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper, we consider a robust regression estimator when the interest random variable is subject to random right-censoring. Based on the so-called synthetic data, we define a new kernel estimator. Under classical conditions and using a VC-classes theory, we establish its uniform consistency with rate and asymptotic normality properties. Special cases are studied and simulations are drawn to illustrate the main results.
引用
收藏
页码:505 / 525
页数:20
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