Nonparametric relative regression under random censorship model

Abstract

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.