funFEM (version 1.2)

funFEM-package: Model-based clustering in the discriminative functional subspaces with the funFEM algorithm

Description

The package provides the funFEM algorithm (Bouveyron et al., 2014) which allows to cluster functional data by modeling the curves within a common and discriminative functional subspace.

Details

Package:	funFEM
Type:	Package
Version:	1.0
Date:	2014-09-06
License:	GPL-2

References

C. Bouveyron, E. C<U+00F4>me and J. Jacques, The discriminative functional mixture model for the analysis of bike sharing systems, Preprint HAL n.01024186, University Paris Descartes, 2014.

Examples

# NOT RUN {
# Clustering the well-known "Canadian temperature" data (Ramsay & Silverman)
basis <- create.bspline.basis(c(0, 365), nbasis=21, norder=4)
fdobj <- smooth.basis(day.5, CanadianWeather$dailyAv[,,"Temperature.C"],basis,
        fdnames=list("Day", "Station", "Deg C"))$fd
res = funFEM(fdobj,K=4)

# Visualization of the partition and the group means
par(mfrow=c(1,2))
plot(fdobj,col=res$cls,lwd=2,lty=1)
fdmeans = fdobj; fdmeans$coefs = t(res$prms$my)
plot(fdmeans,col=1:max(res$cls),lwd=2)
# }