funHDDC: Univariate and Multivariate Model-Based Clustering in Group-Specific Functional Subspaces

The funHDDC algorithm (Bouveyron and Jacques, 2001, Schmutz et al., 2017) allows to cluster functional univariate or multivariate data by modeling each group within a specific functional subspace.

Version: 2.0
Depends: MASS, fda, R (≥ 3.1.0)
Published: 2018-04-18
Author: A Schmutz, J. Jacques & C. Bouveyron
Maintainer: Charles Bouveyron <charles.bouveyron at>
License: GPL-2
NeedsCompilation: no
In views: Cluster, FunctionalData
CRAN checks: funHDDC results


Reference manual: funHDDC.pdf
Package source: funHDDC_2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: funHDDC_2.0.tgz, r-oldrel: funHDDC_2.0.tgz
Old sources: funHDDC archive

Reverse dependencies:

Reverse suggests: funcy


Please use the canonical form to link to this page.