Model-based clustering of functional data

Julien Jacques (1, 2) , Cristian Preda (1, 2)

1 LPP - Laboratoire Paul Painlevé - UMR 8524
2 MODAL - MOdel for Data Analysis and Learning

Model-based clustering for functional data is considered. An alternative to model-based clustering using the functional principal components is proposed by approximating the density of functional random variables. The EM algorithm is used for parameter estimation and the maximum a posteriori rule provides the clusters. Simulation study and real data application illustrate the interest of the proposed methodology.

Mots clés: functional data; functional principal component analysis; model-based clustering; random function density; EM algorithm

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Julien Jacques, Cristian Preda. Model-based clustering of functional data. 2011. ⟨hal-00628247v1⟩