Nonparametric density estimators based on nonstationary absolutely regular random sequences
Summary: 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.
nonstationary absolutely regular random sequences
scientific article; zbMATH DE number 947008