Visualization and Analysis of Multiple Time Series by Beanplot PCA

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• 作者：Carlo Drago (7)
  Carlo Natale Lauro (8)
  Germana Scepi (8)
  
  7. University of Rome 鈥淣iccolo Cusano鈥? Via Don Carlo Gnocchi 3 ; 20016 ; Roma ; Italy
  8. University of Naples 鈥淔ederico II鈥? Via Cinthia 26 ; 80126 ; Naples ; Italy
  
• 关键词：Beanplots ; Symbolic data analysis
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9047
• 期：1
• 页码：147-155
• 全文大小：472 KB
• 参考文献：1. A.A.V.V. R Graph Gallery. http://gallery.r-enthusiasts.com/ (2013)
  2. Arroyo, J, Mat茅, C (2009) Forecasting histogram time series with k-nearest neighbours methods. International Journal of Forecasting 25: pp. 192-207 CrossRef
  3. Billard, L, Diday, E (2003) From the Statistics of Data to the Statistics of Knowledge. Journal of the American Statistical Association 98: pp. 470-487 CrossRef
  4. Drago, C., Scepi, G.: Visualizing and exploring high frequency financial data: beanplot time series. In: New Perspectives in Statistical Modeling and Data Analysis: Proceedings of the 7th Conference of the Classification and Data Analysis Group of the Italian Statistical Society, Catania, 2009, vol. 7, p. 283. Springer (9鈥?1 September 2011)
  5. Drago, C., Scepi, G.: Time Series Clustering from High Dimensional Data. Working Paper also presented at CHDD 2012 International Workshop on Clustering High Dimensional Data, Napoli, May 2012
  6. Drago, C., Lauro, C., Scepi, G.: Beanplot Data Analysis in a Temporal Framework Workshop in Symbolic Data Analysis. Working Paper also presented at eight Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Pavia, September 2011
  7. Du, J.: Combined algorithms for constrained estimation of finite mixture distributions with grouped data and conditional data (Doctoral dissertation, McMaster University) (2002)
  8. Kampstra, P (2008) Beanplot: A Boxplot Alternative for Visual Comparison of Distributions. Journal Of Statistical Software 28: pp. 1-9
  9. Macdonald, P. and with contributions from Du, J. mixdist: Finite Mixture Distribution Models. R package (2012)
  10. Sheng, HY, Walker, JJ, Ogren, DE (1986) A stepwise method for determining the number of component distributions in a mixture. Mathematical Geology 18: pp. 153-160 CrossRef
  11. Sheather, SJ, Jones, C (1991) A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society Series B Methodological 53: pp. 683-690
  12. Verde, R., Irpino, A.: Dynamic clustering of histogram data: using the right metric. In: Brito, P., Bertrand, P., Cucumel, G., De Carvalho, F.: Selected contributions in data analysis and classification, pp. 123鈥?34. Springer, Berlin (2007)
  
• 作者单位：Statistical Learning and Data Sciences
• 丛书名：978-3-319-17090-9
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Beanplot 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.