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Nonparametric density estimators based on nonstationary absolutely regular random sequences. (English) Zbl 0897.62036
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.

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)
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