M-estimation of the regression function under random left truncation and functional time series model

被引：0
作者：
Saliha Derrar
Ali Laksaci
Elias Ould Saïd
机构：
[1] Université de Sidi Bel Abbès,Laboratoire de Statistique et Processus Stochastiques
[2] ULCO,Department of Mathematics, College of Science
[3] LMPA,undefined
[4] IUT de Calais,undefined
[5] King Khalid University,undefined
来源：
Statistical Papers | 2020年 / 61卷
关键词：
Asymptotic normality; Functional data; Kernel estimator; Lynden-Bell estimator; Robust estimation; Small balls probabilities; Strong consistency; Truncated data; 60G42; 62F12; 62G20; 62G05;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper we study the M-estimation of the functional nonparametric regression when the response variable is subject to left-truncation by an other random variable. Under standard assumptions, we get the almost complete convergence rate of this robust estimate when the sample is an α\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}-mixing sequence. This approach can be applied in time series analysis to the prediction problem. Our asymptotic results are confronted by some simulations study.
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页码：1181 / 1202
页数：21
相关论文
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