Asymptotic normality and Berry-Esseen results for conditional density estimator with censored and dependent data

被引:10
|
作者
Liang, Han-Ying [1 ]
Peng, Liang [2 ]
机构
[1] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China
[2] Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA
关键词
alpha-mixing; Asymptotic normality; Berry-Esseen type bound; Censored data; Conditional density; KAPLAN-MEIER ESTIMATE; NONPARAMETRIC-ESTIMATION; TIME-SERIES; CONVERGENCE; SEQUENCES; SUMS;
D O I
10.1016/j.jmva.2010.01.002
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper we derive the asymptotic normality and a Berry-Esseen type bound for the kernel conditional density estimator proposed in Ould-Said and Cai (2005) 1261 when the censored observations with multivariate covariates form a stationary alpha-mixing sequence. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:1043 / 1054
页数:12
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