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Space-Time FPCA Clustering of Multidimensional Curves

  • Giada Adelfio
  • Francesca Di Salvo
  • Marcello Chiodi
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 227)

Abstract

In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.

Keywords

FPCA Clustering of multidimensional curves GAM Spatio-temporal pattern 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Giada Adelfio
    • 1
  • Francesca Di Salvo
    • 1
  • Marcello Chiodi
    • 1
  1. 1.Dipartimento Scienze Economiche Aziendali e StatistichePalermoItaly

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