Nalini Ravishanker, Lilian S.Y. Wu, et al.
Journal of Statistical Computation and Simulation
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. © 2010 Springer Science+Business Media, LLC.
Nalini Ravishanker, Lilian S.Y. Wu, et al.
Journal of Statistical Computation and Simulation
Jonathan R.M. Hosking, Edwin P.D. Pednault, et al.
Future Generation Computer Systems
Nalini Ravishanker, Edward L. Melnick, et al.
Journal of Time Series Analysis
Hongfei Li, Lloyd A. Treinish, et al.
IBM J. Res. Dev