Comparison of time series with unequal length in the frequency domain
AbstractIn statistical data analysis it is often important to compare, classify, and cluster different time series. For these purposes various methods have been proposed in the literature, but they usually assume time series with the same sample size. In this paper, we propose a spectral domain method for handling time series of unequal length. The method make the spectral estimates comparable by producing statistics at the same frequency. The procedure is compared with other methods proposed in the literature by a Monte Carlo simulation study. As an illustrative example, the proposed spectral method is applied to cluster industrial production series of some developed countries.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 15310.
Date of creation: Apr 2009
Date of revision:
Autocorrelation function; Cluster analysis; Interpolated periodogram; Reduced periodogram; Spectral analysis; Time series; Zero-padding.;
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; Diffusion Processes
- C0 - Mathematical and Quantitative Methods - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-05-30 (All new papers)
- NEP-ECM-2009-05-30 (Econometrics)
- NEP-ETS-2009-05-30 (Econometric Time Series)
- NEP-FOR-2009-05-30 (Forecasting)
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