Nonparametric relative regression under random censorship model

In this paper we define and study a new estimator of the regression function when the response random variable is subject to random right-censoring. The estimator is constructed by minimizing the mean squared relative error of the regression operator where outlier data are present and the response v...

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Bibliographic Details
Published inStatistics & probability letters Vol. 151; pp. 116 - 122
Main Authors Salah, Khardani, Yousri, Slaoui
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.08.2019
Elsevier
Subjects
Asymptotic normality
Censored data
Consistency
Mean squared relative error
Relative regression
Statistics
Censored data
Relative regression
Mean squared relative error
Asymptotic normality
Consistency
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ISSN0167-7152
1879-2103
DOI10.1016/j.spl.2019.03.019

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Summary:In this paper we define and study a new estimator of the regression function when the response random variable is subject to random right-censoring. The estimator is constructed by minimizing the mean squared relative error of the regression operator where outlier data are present and the response variable of the model is positive. Under classical conditions we establish the uniform consistency with rate over a compact set and asymptotic normality of the estimator suitably normalized. The asymptotic variance is explicitly given.
ISSN:0167-7152
1879-2103
DOI:10.1016/j.spl.2019.03.019