On the robustification of the kernel estimator of the functional modal regression

被引：0
|
作者：
Amel, Azzi [1 ]
Ali, Laksaci [2 ]
Elias, Ould Said [3 ]
机构：
[1] Ctr Univ Salhi Ahmed Naama, Naama, Algeria
[2] King Khalid Univ, Dept Math, Coll Sci, POB 9004, Abha 62529, Saudi Arabia
[3] Univ Littoral Cote dOpale, Lab Math Pures & Appl, IUT Calais, 19 Rue Louis David Calais, F-62228 Dunkerque, France
来源：
STATISTICS & PROBABILITY LETTERS | 2022年 / 181卷
关键词：
Conditional mode estimate; Functional statistics; Quantile regression; Robust estimator; CONDITIONAL MODE; QUANTILE REGRESSION; ASYMPTOTIC NORMALITY;
D O I：
10.1016/j.spl.2021.109256
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：
A new nonparametric estimator of the conditional mode when the regressors are functionals is proposed. The main aim of this paper is to establish the almost complete convergence (with rate) of the constructed estimator is estimate under general assumptions in nonparametric functional statistics. A simulation study is carried out to examine, illustrate, the finite samples behavior of the constructed estimator. Finally, a discussion highlighting the impact of this new estimator in nonparametric functional data analysis is also given. (C) 2021 Elsevier B.V. All rights reserved.
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页数：8
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