Functional Latent Data Models for Clustering Heterogeneous Curves ('FLaMingos')

Provides a variety of original and flexible user-friendly statistical latent variable models for the simultaneous clustering and segmentation of heterogeneous functional data (i.e time series, or more generally longitudinal data, fitted by unsupervised algorithms, including EM algorithms. Functional Latent Data Models for Clustering heterogeneous curves ('FLaMingos') are originally introduced and written in 'Matlab' by Faicel Chamroukhi <>. The references are mainly the following ones. Chamroukhi F. (2010) <>. Chamroukhi F., Same A., Govaert, G. and Aknin P. (2010) . Chamroukhi F., Same A., Aknin P. and Govaert G. (2011). . Same A., Chamroukhi F., Govaert G. and Aknin, P. (2011) . Chamroukhi F., and Glotin H. (2012) . Chamroukhi F., Glotin H. and Same A. (2013) . Chamroukhi F. (2015) <>. Chamroukhi F. and Nguyen H-D. (2019) .


Reference manual

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0.1.0 by Florian Lecocq, a year ago

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Authors: Faicel Chamroukhi [aut] , Florian Lecocq [aut, trl, cre] (R port) , Marius Bartcus [aut, trl] (R port)

Documentation:   PDF Manual  

GPL (>= 3) license

Imports methods, stats, Rcpp

Suggests knitr, rmarkdown

Linking to Rcpp, RcppArmadillo

See at CRAN