Using independent component for clustering of time series data

Abstract

In this work we propose the use of independent component analysis for clustering time series. Considering different numbers of independent components, the complete linkage method was used to identify groups based on the estimated coefficients of the mixing matrix. The use of independent component analysis not only enables the clustering of time series as also provides us with information about the characteristics common to groups from the analysis of the components. The analysis is exemplified for time series of sea levels in different countries during the period of 26 years. The dendrogram obtained for 2 independent components showed four groups: one contains only Hong Kong, the second is formed by Malaysia and Thailand. The other two groups are formed by Australia, New Zealand and Brazil, Japan, Alaska, Singapore and Norway. We have shown that, using data sea level, the independent component analysis can reveal the underlying structure in the database and is a powerful tool for clustering of time series.