A functional data based method for time series classification
AbstractWe propose using the integrated periodogram to classify time series. The method assigns a new element to the group minimizing the distance from the integrated periodogram of the element to the group mean of integrated periodograms. Local computation of these periodograms allows the application of the approach to nonstationary time series. Since the integrated periodograms are functional data, we apply depth-based techniques to make the classification robust. The method provides small error rates with both simulated and real data, and shows good computational behaviour.
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Bibliographic InfoPaper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws087427.
Date of creation: Jan 2009
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Time series; Classification; Integrated periodogram; Data depth;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-01-10 (All new papers)
- NEP-ECM-2009-01-10 (Econometrics)
- NEP-ETS-2009-01-10 (Econometric Time Series)
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