Asymptotic normality of wavelet density estimator under censored dependent observations

被引：0
|
作者：
Niu, Si-li [1 ]
机构：
[1] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China
来源：
ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2012年 / 28卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Wavelet density estimator; asymptotic normality; censored data; alpha-mixing; random weighted estimator; HAZARD RATE ESTIMATION; ERROR; RATES;
D O I：
10.1007/s10255-012-0188-9
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we discuss the asymptotic normality of the wavelet estimator of the density function based on censored data, when the survival and the censoring times form a stationary alpha-mixing sequence. To simulate the distribution of estimator such that it is easy to perform statistical inference for the density function, a random weighted estimator of the density function is also constructed and investigated. Finite sample behavior of the estimator is investigated via simulations too.
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页码：781 / 794
页数：14
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