funFEM-package: Model-based clustering in the discriminative functional...

In funFEM: Clustering in the Discriminative Functional Subspace

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

Author(s)

Charles Bouveyron

Maintainer: <[e-mail]>

References

C. Bouveyron, E. Côme and J. Jacques, The discriminative functional mixture model for the analysis of bike sharing systems, Preprint HAL n.01024186, University Paris Descartes, 2014.

Examples

# 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)

Example output

Loading required package: MASS
Loading required package: fda
Loading required package: splines
Loading required package: Matrix

Attaching package: 'fda'

The following object is masked from 'package:graphics':

    matplot

Loading required package: elasticnet
Loading required package: lars
Loaded lars 1.2

The "ward" method has been renamed to "ward.D"; note new "ward.D2"
[1] "done"
[1] "done"

funFEM documentation built on Oct. 27, 2021, 5:08 p.m.