Abstract
AbstractBeanplot time series have been introduced by the authors as an aggregated data representation, in terms of peculiar symbolic data, for dealing with large temporal datasets. In the presence of multiple beanplot time series it can be very interesting for interpretative aims to find useful syntheses. Here we propose an extension, based on PCA, of the previous approach to multiple beanplot time series. We show the usefulness of our proposal in the context of the analysis of different financial markets.KeywordsBeanplotsSymbolic data analysis
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