An Exploratory Analysis of Multiple Multivariate Time Series

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 variancecovariance matrices are generalized to lagged cross-autocorrelation matrices. 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.

• Type: Journal
• Year: 2015
• Where: PKDD
• Authors: Lynne Billard, Ahlame Douzal Chouakria, Seyed Yaser Samadi
• Keywords: Data Mining, PKDD 2015