Funclustering

The code was originally on an R-forge repository.

This package proposes a model-based clustering algorithm for multivariate functional data. The parametric mixture model, based on the assumption of normality of the principal components resulting from a multivariate functional PCA, is estimated by an EM-like algorithm. The main advantage of the proposed algorithm is its ability to take into account the dependence among curves.

Installation

From github:

library(devtools)
install_github("modal-inria/Funclustering")

Credits

Funclustering is developed by Mohamed Soueidatt, Julien Jacques and Christophe Biernacki with contribution of Vincent Kubicki and Quentin Grimonprez

Copyright Inria - Université de Lille

Licence

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

References

• J.Jacques and C.Preda (2013), Funclust: a curves clustering method using functional random variable density approximation, Neurocomputing, 112, 164-171.
• J.Jacques and C.Preda (2013), Model-based clustering of multivariate functional data, Computational Statistics and Data Analysis, in press DOI 10.1016/j.csda.2012.12.004.