Title :

Model-based clustering for multivariate functional data

Author(s) :

Jacques, Julien [Auteur]
Preda, Cristian [Auteur]

Journal title :

Computational Statistics and Data Analysis

Volume number :

71

Pages :

92-106

Publisher :

Elsevier

Publication date :

2014-06-01

ISSN :

0167-9473

Keyword(s) :

Multivariate functional data
Density approximation
Model-based clustering
Multivariate functional principal component analysis
EM algorithm

HAL domain(s) :

Mathématiques [math]/Statistiques [math.ST]

English abstract : [en]

This paper proposes the first model-based clustering algorithm for multivariate functional data. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, {based on the ...
Show more >This paper proposes the first model-based clustering algorithm for multivariate functional data. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, {based on the assumption of normality of the principal components}, is defined and estimated by an EM-like algorithm. The main advantage of the proposed model is its ability to take into account the dependence among curves. Results on simulated and real datasets show the efficiency of the proposed method.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

CNRS
Université de Lille

Collections :

• METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694

Submission date :

2020-06-08T14:11:37Z
2020-06-09T09:11:41Z