Spectral density estimation for nonstationary data with nonzero mean function
Résumé
We introduce a new approach for nonparametric spectral density estimation based on the subsampling technique, which we apply to the important class of nonstation-ary time series. These are almost periodically correlated sequences. In contrary to existing methods our technique does not require demeaning of the data. On the simulated data examples we compare our estimator of spectral density function with the classical one. Additionally, we propose a modified estimator, which allows to reduce the leakage effect. Moreover, we provide two real data economic applications.
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Origine : Fichiers produits par l'(les) auteur(s)
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