Strong consistency of the local linear relative regression estimator for censored data

In this paper, we combine the local linear approach to the relative error regression estimation method to build a new estimator of the regression operator when the response variable is subject to random right censoring. We establish the uniform almost sure consistency with rate over a compact set of...

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Published inRocznik Akademii Górniczo-Hutniczej im. Stanisława Staszica. Opuscula Mathematica Vol. 42; no. 6; pp. 805 - 832
Main Authors Bouhadjera, Feriel, Said, Elias Ould
Format Journal Article
LanguageEnglish
Published AGH University of Science and Technology 01.01.2022
AGH Univeristy of Science and Technology Press
Subjects
censored data
local linear approach
Mathematics
regression function
relative error
Statistics
uniform almost sure convergence
local linear approach
censored data
relative error
regression function
uniform almost sure convergence
Online AccessGet full text
ISSN1232-9274
2300-6919
DOI10.7494/OpMath.2022.42.6.805

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Summary:In this paper, we combine the local linear approach to the relative error regression estimation method to build a new estimator of the regression operator when the response variable is subject to random right censoring. We establish the uniform almost sure consistency with rate over a compact set of the proposed estimator. Numerical studies, firstly on simulated data, then on a real data set concerning the death times of kidney transplant patients, were conducted. These practical studies clearly show the superiority of the new estimator compared to competitive estimators.
ISSN:1232-9274
2300-6919
DOI:10.7494/OpMath.2022.42.6.805