Relative error prediction from censored data under α-mixing condition

In this paper, we address the case of a randomly right-censored model when the data exhibit some kind of dependency. We build and study a new nonparametric regression estimator by using the mean squared relative error as a loss function. Under classical conditions, we establish the uniform consistency with rate and asymptotic normality of the estimator suitably normalized.