Comparison of presmoothing methods in kernel density estimation under censoring

被引：0

作者：

M. A. Jácome

I. Gijbels

R. Cao

机构：

[1] Universidade da Coruña,Departamento de Matemáticas, Facultad de Ciencias

[2] Katholieke Universiteit Leuven,Department of Mathematics and University Center for Statistics

[3] Universidade da Coruña,Departamento de Matemáticas, Facultad de Informática

来源：

Computational Statistics | 2008年 / 23卷

关键词：

Censored data; Kaplan–Meier estimator; Local linear fit; Nadaraya–Watson smoother; Survival analysis;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The behavior of the presmoothed density estimator is studied when different ways to estimate the conditional probability of uncensoring are used. The Nadaraya–Watson, local linear and local logistic approach are compared via simulations with the classical Kaplan–Meier estimator. While the local logistic presmoothing estimator presents the best performance, the relative benefits of the local linear versus the Nadaraya–Watson estimator depend very much on the shape of some underlying functions.

引用

页码：381 / 406

页数：25

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