An interpolated periodogram-based metric for comparison of time series with unequal lengths
AbstractWe propose a periodogram-based metric for classification and clustering of time series with different sample sizes. For such cases, we know that the Euclidean distance between the periodogram ordinates cannot be used. One possible way to deal with this problem is to interpolate lineary one of the periodograms in order to estimate ordinates of the same frequencies.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 2075.
Date of creation: 2006
Date of revision:
Classification; Cluster analysis; Interpolation; Periodogram; Time series;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-03-17 (All new papers)
- NEP-ECM-2007-03-17 (Econometrics)
- NEP-ETS-2007-03-17 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Caiado, Jorge & Crato, Nuno & Pena, Daniel, 2006. "A periodogram-based metric for time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2668-2684, June.
- Maharaj, Elizabeth Ann, 2002.
"Comparison of non-stationary time series in the frequency domain,"
Computational Statistics & Data Analysis,
Elsevier, vol. 40(1), pages 131-141, July.
- Maharaj, E.A., 2001. "Comparison of Non-Stationary Time Series in the Frequency Domain," Monash Econometrics and Business Statistics Working Papers 1/01, Monash University, Department of Econometrics and Business Statistics.
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