Model-based clustering for multivariate ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Model-based clustering for multivariate functional data
Author(s) :
Jacques, Julien [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Preda, Cristian [Auteur]
MOdel for Data Analysis and Learning [MODAL]
MOdel for Data Analysis and Learning [MODAL]
Preda, Cristian [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Journal title :
Computational Statistics and Data Analysis
Pages :
92-106
Publisher :
Elsevier
Publication date :
2014-03
ISSN :
0167-9473
English keyword(s) :
Multivariate functional data
density approximation
model-based clustering
multivariate functional principal component analysis
EM algorithm
density approximation
model-based clustering
multivariate functional principal component analysis
EM algorithm
HAL domain(s) :
Mathématiques [math]/Statistiques [math.ST]
Statistiques [stat]/Théorie [stat.TH]
Statistiques [stat]/Théorie [stat.TH]
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 >
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
Popular science :
Non
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