KERNEL ESTIMATION OF HIGHER DERIVATIVES OF DENSITY AND HAZARD RATE FUNCTION FOR TRUNCATED AND CENSORED DEPENDENT DATA

被引：0

作者：

陈清平

戴永隆

机构：

[1] Department of Statistics

[2] Wuhan University

[3] Wuhan

[4] China Wuhan University of Science and Technology

[5] China

[6] Zhongshan University

[7] Guangzhou

来源：

Acta Mathematica Scientia | 2003年 / 04期

关键词：

Truncated and censored data; α-mixing; strong consistency; law of iterated logarithm; mode;

D O I：

暂无

中图分类号：

O211.67 [期望与预测];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

<正> Based on left truncated and right censored dependent data, the estimators of higher derivatives of density function and hazard rate function are given by kernel smoothing method. When observed data exhibit α-mixing dependence, local properties including strong consistency and law of iterated logarithm are presented. Moreover, when the mode estimator is defined as the random variable that maximizes the kernel density estimator, the asymptotic normality of the mode estimator is established.

引用

页码：477 / 486

页数：10