Relative Error Prediction for Twice Censored Data

Abstract

In this paper we consider the problem of non-parametric relative regression for twice censored data. We introduce and study a new estimate of the regression function when it is appropriate to assess performance in terms of mean squared relative error of prediction. 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. A Monte Carlo study is carried out to evaluate the performance of this estimate.