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.

引用

页码：1043 / 1054

页数：12

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