Comparison of presmoothing methods in kernel density estimation under censoring

被引：11

作者：

Jacome, M. A. ^{[1
]}

Gijbels, I. ^{[2
,3
]}

Cao, R. ^{[4
]}

机构：

[1] Univ A Coruna, Fac Ciencias, Dept Math, La Coruna 15071, Spain

[2] Katholieke Univ Leuven, Dept Math, B-3001 Louvain, Belgium

[3] Katholieke Univ Leuven, Univ Ctr Stat, B-3001 Louvain, Heverlee, Belgium

[4] Univ A Coruna, Fac Informat, Dept Math, La Coruna 15071, Spain

来源：

COMPUTATIONAL STATISTICS | 2008年 / 23卷 / 03期

关键词：

censored data; Kaplan-Meier estimator; local linear fit; Nadaraya-Watson smoother; survival analysis;

D O I：

10.1007/s00180-007-0076-6

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：

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：26

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