Harel, Michel; Puri, Madan L. Nonparametric density estimators based on nonstationary absolutely regular random sequences. (English) Zbl 0897.62036 J. Appl. Math. Stochastic Anal. 9, No. 3, 233-254 (1996). 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. Cited in 3 Documents MSC: 62G07 Density estimation 60F05 Central limit and other weak theorems 62G20 Asymptotic properties of nonparametric inference 62M05 Markov processes: estimation; hidden Markov models 62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH) Keywords:density estimators; nonstationary absolutely regular random sequences; strong mixing; phi-mixing; central limit theorems; ARMA processes PDFBibTeX XMLCite \textit{M. Harel} and \textit{M. L. Puri}, J. Appl. Math. Stochastic Anal. 9, No. 3, 233--254 (1996; Zbl 0897.62036) Full Text: DOI EuDML