funFEM: an R package for functional data clustering
Charles Bouveyron, Julien Jacques · HAL (Le Centre pour la Communication Scientifique Directe) · 2015
A new model-based clustering algorithm for times series (or more generally functional data), called FunFEM, has been proposed in Bouveyron et al. (2015). It is based on a functional mixture model which allows the clustering of the data in a discriminative functional subspace. This model presents the advantage to be parsimonious and to allow the visualization of the clustered systems. This paper presents the funFEM package for R which implements this new clustering algorithm.