Kernel regression uniform rate estimation for censored data under α-mixing condition

被引：15

作者：

Guessoum, Zohra ^{[3
]}

Said, Elias Ould ^{[1
,2
]}

机构：

[1] Univ Lille Nord France, F-59000 Lille, France

[2] LMPA, ULCO, F-62000 Calais, France

[3] Univ Sci Tech Houari Boumediene, Fac Math, Lab MSTD, El Alia 16111, Algeria

来源：

ELECTRONIC JOURNAL OF STATISTICS | 2010年 / 4卷

关键词：

Censored data; Kernel estimator; nonparametric regression; rate of convergence; strong consistency; strong mixing; NONPARAMETRIC-ESTIMATION;

D O I：

10.1214/08-EJS195

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 behavior of a kernel estimator of the regression function in the right censored model with a-mixing data. The uniform strong consistency over a real compact set of the estimate is established along with a rate of convergence. Some simulations are carried out to illustrate the behavior of the estimate with different examples for finite sample sizes.

引用

页码：117 / 132

页数：16

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