Robust functional classification for time series
We propose using the integrated periodogram to classify time series. The method assigns a new time series to the group that minimizes the distance between the time series integrated periodogram and the group mean of integrated periodograms. Local computation of these periodograms allows to apply this approach to nonstationary time series. Since the integrated periodograms are curves, we apply functional data depth-based techniques to make the classification robust. The method provides small error rates with both simulated and real geological data, improving on existing approaches, and presents good computational behavior.
Palabras clave: time series classification integrated periodogram functional data depth
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22/04/12
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