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: 2.3.0
Depends: MASS, fda, R (≥ 3.1.0)
Suggests: knitr, rmarkdown
Published: 2019-04-19
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
Vignettes: funHDDC
Package source: funHDDC_2.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: funHDDC_2.3.0.tgz, r-oldrel: funHDDC_2.3.0.tgz
Old sources: funHDDC archive


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