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Comparison and Classification of Stationary Multivariate Time Series

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journal contribution
posted on 07.06.2017, 05:19 by Maharaj, Ann
Time series often have patterns that form a basis for comparing them or classifying them into groups. Pattern recognition of time series arises in a number of practical situations. Procedures for the comparison and classification of univariate stationary series already exist in the literature. A famous application is the comparison and classification of earthquake and nuclear explosion waveforms - Shumway (1982). In this paper we present procedures to compare and classify stationary multivariate time series. Simulations studies show that the procedures perform fairly well for reasonably long series.


Year of first publication



Department of Econometrics and Business Statistics.