Nonparametric inference for the proportionality function in the random censorship model

被引：0

作者：

Hollander, M ^{[1
]}

Laird, G

Song, KS

机构：

[1] Florida State Univ, Dept Stat, Tallahassee, FL 32306 USA

[2] Florida State Univ, Ctr Stat Consulting, Tallahassee, FL 32306 USA

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2003年 / 15卷 / 02期

基金：

美国国家卫生研究院;

关键词：

random censorship model; proportional hazards model; nonparametric estimation; proportionality function; weak convergence; uniform convergence;

D O I：

10.1080/1048525031000089329

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：

By generalizing the proportional hazards model, we introduce a new function beta(t), which we call the proportionality function, and which we show plays a role in studying aspects of the randomly censored model. We develop an asymptotically efficient nonparametric estimator of beta(t), establish its uniform consistency, and obtain a weak convergence result. Furthermore, a confidence band for beta(t), based on the bootstrap, is developed. The results are applied to an actual dataset.

引用

页码：151 / 169

页数：19

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