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Spectrum-Based Comparison of Stationary Multivariate Time Series

Author

Listed:
  • Nalini Ravishanker

    (University of Connecticut)

  • J. R. M. Hosking

    (IBM Research Division)

  • Jaydip Mukhopadhyay

    (Bristol Myers Squibb)

Abstract

The problem of comparison of several multivariate time series via their spectral properties is discussed. A pairwise comparison between two independent multivariate stationary time series via a likelihood ratio test based on the estimated cross-spectra of the series yields a quasi-distance between the series. A hierarchical clustering algorithm is then employed to compare several time series given the quasi-distance matrix. For use in situations where components of the multivariate time series are measured in different units of scale, a modified quasi-distance based on a profile likelihood based estimation of the scale parameter is described. The approach is illustrated using simulated data and data on daily temperatures and precipitations at multiple locations. A comparison between hierarchical clustering based on the likelihood ratio test quasi-distance and a quasi-distance described in Kakizawa et al. (J Am Stat Assoc 93:328–340, 1998) is interesting.

Suggested Citation

  • Nalini Ravishanker & J. R. M. Hosking & Jaydip Mukhopadhyay, 2010. "Spectrum-Based Comparison of Stationary Multivariate Time Series," Methodology and Computing in Applied Probability, Springer, vol. 12(4), pages 749-762, December.
    • Handle: RePEc:spr:metcap:v:12:y:2010:i:4:d:10.1007_s11009-010-9180-0
    DOI: 10.1007/s11009-010-9180-0
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    References listed on IDEAS

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    1. D. S. Coates & P. J. Diggle, 1986. "Tests For Comparing Two Estimated Spectral Densities," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(1), pages 7-20, January.
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