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

The funHDDC algorithm (Schmutz et al., 2018) allows to cluster functional univariate or multivariate data by modeling each group within a specific functional subspace.

Version: 2.2.0
Depends: MASS, fda, R (≥ 3.1.0)
Suggests: knitr, rmarkdown
Published: 2018-10-08
Author: A Schmutz, J. Jacques & C. Bouveyron
Maintainer: Charles Bouveyron <charles.bouveyron at gmail.com>
License: GPL-2
NeedsCompilation: no
In views: Cluster, FunctionalData
CRAN checks: funHDDC results

Downloads:

Reference manual: funHDDC.pdf
Vignettes: funHDDC
Package source: funHDDC_2.2.0.tar.gz
Windows binaries: r-devel: funHDDC_2.2.0.zip, r-release: funHDDC_2.2.0.zip, r-oldrel: funHDDC_2.2.0.zip
OS X binaries: r-release: funHDDC_2.2.0.tgz, r-oldrel: funHDDC_2.2.0.tgz
Old sources: funHDDC archive

Reverse dependencies:

Reverse suggests: funcy

Linking:

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