Asymptotic normality of the kernel estimator of the recursive density under the censored \(\beta \)-mixing model

Abstract

In this paper, we establish the asymptotic normality of the recursive estimator of the density function for the right-censored random model when the data present some form of dependence. It is assumed that, the survival and the censoring times form a stationary \(\beta\)-mixing-mixing. Therefore this paper is part of this vast project aimed to extending the results obtained with independent variables in the dependent case.