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Li, Ta-Hsin; Kedem, Benjamin; Yakowitz, Sid

Asymptotic normality of sample autocovariances with an application in frequency estimation. (English) Zbl 0814.62056

Stochastic Processes Appl. 52, No. 2, 329-349 (1994).
Summary: The asymptotic normality of sample autocovariances is proved for time series with mixed-spectra, which extends the classical results of Bartlett for linear processes. It is also shown that the asymptotic normality remains valid after linear filtering, if the filter is strictly stable so that the end-point effect of finite samples can be ignored. The developed theory is then employed to establish the asymptotic normality of a recently proposed fast frequency estimation procedure.

Cited in 4 Documents

MSC:

62M15 Inference from stochastic processes and spectral analysis
62E20 Asymptotic distribution theory in statistics
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62M07 Non-Markovian processes: hypothesis testing

Keywords:

frequency estimation; asymptotic normality of sample autocovariances; time series; mixed-spectra; linear filtering
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References:

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