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Contribution to Book
VISUALIZATION AND ANALYSIS OF LARGE DATASETS BY BEANPLOT PCA
Advances in Latent Variables (2013)
  • Carlo Drago
  • Carlo Lauro
  • Germana Scepi
Abstract

Advances in computer technology have made large data ubiquitous and have determined the need to handles these data accordingly. In particular these data need to be aggregated using some function, 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 distribution can represent the original data accordingly and contribute to solve 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 building synthesis of multiple beanplot time series as indicators which can have relevant applications in Finance, in Risk Management and in other disciplines.

Keywords
  • Beanplots,
  • Time Series,
  • Symbolic Data Analysis,
  • Principal Component Analysis
Publication Date
Summer June 17, 2013
Editor
Brentari E., Carpita M.
Publisher
Vita e Pensiero
ISBN
978 88 343 2556 8
Citation Information
Carlo Drago, Carlo Lauro and Germana Scepi. "VISUALIZATION AND ANALYSIS OF LARGE DATASETS BY BEANPLOT PCA" Milan, ItalyAdvances in Latent Variables (2013)
Available at: http://works.bepress.com/carlo_drago/120/