Visualization and Analysis of Large Datasets by Beanplot PCA

Advances in computer technology have made large data ubiquitous and have determined the need to handle these data accordingly. In particular they need to be aggregated using some functions, but this process can lead to a loss of information. Beanplot series, in this context, can represent a solution in terms of special symbolic data: in fact the parameters of the density models based on a mixture of distributions represent the original data accordingly and contribute to solving the problem of data storage. In this work we propose an approach to beanplot data analysis by PCA on the parameters of the models. The aim is to build a synthesis of multiple beanplot time series as indicators which can have relevant applications in Finance, in Risk Management and in other disciplines.