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An Exploratory Analysis of Multiple Multivariate Time Series

Lynne Billard 1 Ahlame Douzal-Chouakria 2 Yaser Seyed
1 University of Georgia [USA]
2 LIG - Laboratoire d'Informatique de Grenoble
Abstract : Our aim is to extend standard principal component analysis for non-time series data to explore and highlight the main structure of multiple sets of multivariate time series. To this end, standard variance- covariance matrices are generalized to lagged cross-autocorrelation ma- trices. The methodology produces principal component time series, which can be analysed in the usual way on a principal component plot, except that the plot also includes time as an additional dimension.
Keywords : multivariate time series autocorrelation cross-correlation principal component analysis
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01208416
Contributor : Ahlame Douzal <>
Submitted on : Friday, October 2, 2015 - 3:26:25 PM
Last modification on : Thursday, November 19, 2020 - 12:59:57 PM

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  • HAL Id : hal-01208416, version 1

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CNRS | LIG | UGA

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Lynne Billard, Ahlame Douzal-Chouakria, Yaser Seyed. An Exploratory Analysis of Multiple Multivariate Time Series. ECML-PKDD, Sep 2015, Porto, Portugal. ⟨hal-01208416⟩

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