Asymptotic normality of local linear functional regression estimator based upon censored data

被引：0
|
作者：
Leulmi, Sarra [1 ]
机构：
[1] Univ Bros Mentouri, Dept Math, LAMASD Lab, Constantine, Algeria
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2024年
关键词：
Asymptotic normality; censored data; functional data; local linear estimation; regression function; CONDITIONAL DENSITY; ERROR;
D O I：
10.1080/03610926.2024.2378376
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：
This article is concerned with the local linear non parametric regression estimator of a right censored scalar response random variable, given a functional random covariate. First, we investigate its asymptotic normality under the concentration properties of small ball probability functions. Then, we apply the results to present the asymptotic (1-alpha) confidence interval of the regression function for 0 < alpha < 1. To lend further support to our theoretical results, we carry out a simulation study to illustrate the performance and the asymptotic Gaussian behavior of our estimator. Finally, an application to real data is provided.
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页数：21
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