Spectral estimation in the presence of missing data

In this article we propose a quasi-Whittle estimator for parametric families of time series models in the presence of missing data. This estimator extends results to the incompletely observed case. This extension is valid to non-Gaussian and nonlinear models. It also allows us to bound the variance...

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Veröffentlicht in:Theory of probability and mathematical statistics 2017, Vol.95, p.59-79
Hauptverfasser: Bahamonde, Natalia, Doukhan, Paul
Format: Artikel
Sprache:eng
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Zusammenfassung:In this article we propose a quasi-Whittle estimator for parametric families of time series models in the presence of missing data. This estimator extends results to the incompletely observed case. This extension is valid to non-Gaussian and nonlinear models. It also allows us to bound the variance of an associated quasiperiodogram. A simulation study empirically validates the proposed estimate for mixing and nonmixing models.
ISSN:0094-9000
1547-7363
DOI:10.1090/tpms/1022