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CORR
2010
Springer

Exploratory Analysis of Functional Data via Clustering and Optimal Segmentation

13 years 3 months ago
Exploratory Analysis of Functional Data via Clustering and Optimal Segmentation
We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into K clusters and represents each cluster by a simple prototype (e.g., piecewise constant). The total number of segments in the prototypes, P, is chosen by the user and optimally distributed among the clusters via two dynamic programming algorithms. The practical relevance of the method is shown on two real world datasets. Key words: Functional Data, Multiple time series, Exploratory analysis, Clustering, Segmentation, Dynamic programming
Georges Hébrail, Bernard Hugueney, Yves Lec
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where CORR
Authors Georges Hébrail, Bernard Hugueney, Yves Lechevallier, Fabrice Rossi
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