Unsupervised Curve Clustering using B‐Splines

C. Abraham, P. A. Cornillon, E. Matzner‐Løber and N. Molinari

Scandinavian Journal of Statistics, 2003, vol. 30, issue 3, 581-595

Abstract: Data in many different fields come to practitioners through a process naturally described as functional. Although data are gathered as finite vector and may contain measurement errors, the functional form have to be taken into account. We propose a clustering procedure of such data emphasizing the functional nature of the objects. The new clustering method consists of two stages: fitting the functional data by B‐splines and partitioning the estimated model coefficients using a k‐means algorithm. Strong consistency of the clustering method is proved and a real‐world example from food industry is given.

Date: 2003
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Citations: View citations in EconPapers (49)

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