Quantile estimation for left truncated and right censored data

被引：0

作者：

Zhou, X ^{[1
]}

Sun, LQ

Ren, HB

机构：

[1] Hong Kong Polytech Univ, Dept Appl Math, Kowloon, Hong Kong, Peoples R China

[2] Acad Sinica, Inst Appl Math, Beijing 100080, Peoples R China

[3] Beijing Univ, Dept Stat & Probabil, Beijing 100871, Peoples R China

来源：

STATISTICA SINICA | 2000年 / 10卷 / 04期

关键词：

asymptotic normality; Berry-Esseen type bound; quantile function; kernel estimation; truncated and censored data;

D O I：

暂无

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 study the estimation of a quantile function based on left truncated and right censored data by the kernel smoothing method. Asymptotic normality and a Berry-Esseen type bound for the kernel quantile estimator are derived. Monte Carlo studies are conducted to compare the proposed estimator with the PL-quantile estimator.

引用

页码：1217 / 1229

页数：13

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