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

The funHDDC algorithm allows to cluster functional univariate (Bouveyron and Jacques, 2011, <doi:10.1007/s11634-011-0095-6>) or multivariate data (Schmutz et al., 2018) by modeling each group within a specific functional subspace.

Version: 2.3.1.1
Depends: MASS, fda, R (≥ 3.1.0)
Suggests: knitr, rmarkdown
Published: 2026-05-08
DOI: 10.32614/CRAN.package.funHDDC
Author: A Schmutz [aut], J. Jacques & C. Bouveyron [aut], Julien Jacques [cre]
Maintainer: Julien Jacques <julien.jacques at univ-lyon2.fr>
License: GPL-2
NeedsCompilation: no
CRAN checks: funHDDC results

Documentation:

Reference manual: funHDDC.html , funHDDC.pdf
Vignettes: funHDDC (source, R code)

Downloads:

Package source: funHDDC_2.3.1.1.tar.gz
Windows binaries: r-devel: funHDDC_2.3.1.1.zip, r-release: funHDDC_2.3.1.1.zip, r-oldrel: funHDDC_2.3.1.1.zip
macOS binaries: r-release (arm64): funHDDC_2.3.1.1.tgz, r-oldrel (arm64): funHDDC_2.3.1.1.tgz, r-release (x86_64): funHDDC_2.3.1.1.tgz, r-oldrel (x86_64): funHDDC_2.3.1.1.tgz
Old sources: funHDDC archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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