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Consider a random vector (X, T), where X is d-dimensional and T isone-dimensional. We suppose that the random variable T is subject to randomright censoring and satisfies the $\alpha$-mixing property. The aim of thispaper is to study the behavior of the kernel estimator of the relative errorregression and to establish its uniform almost sure consistency with rate.Furthermore, we have highlighted the covariance term which measures thedependency. The simulation study shows that the proposed estimator performswell for a finite sample size in different cases.

On the strong uniform consistency for relative error of the regression function estimator for censoring times series model