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Spectral estimation in the presence of missing data. (English) Zbl 1411.62249

Theory Probab. Math. Stat. 95, 59-79 (2017) and Teor. Jmovirn. Mat. Stat. 95, 55-74 (2016).
Summary: 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.

MSC:

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62M15 Inference from stochastic processes and spectral analysis
62F12 Asymptotic properties of parametric estimators
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