Nonparametric density estimators based on nonstationary absolutely regular random sequences

Abstract

In this paper, the central limit theorems for the density estimator and for the integrated square error are proved for the case when the underlying sequence of random variables is nonstationary. Applications to Markov processes and ARMA processes are provided.