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
来源：
JOURNAL OF MULTIVARIATE ANALYSIS | 2010年 / 101卷 / 05期
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.
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页码：1043 / 1054
页数：12
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