kml: K-Means for Longitudinal Data

An implementation of k-means specifically design to cluster longitudinal data. It provides facilities to deal with missing value, compute several quality criterion (Calinski and Harabatz, Ray and Turie, Davies and Bouldin, BIC, ...) and propose a graphical interface for choosing the 'best' number of clusters.

Depends: methods, clv, longitudinalData (≥ 2.4)
Published: 2023-12-13
DOI: 10.32614/CRAN.package.kml
Author: Christophe Genolini [cre, aut], Bruno Falissard [ctb], Patrice Kiener [ctb]
Maintainer: Christophe Genolini <christophe.genolini at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: kml citation info
Materials: NEWS
In views: Cluster
CRAN checks: kml results


Reference manual: kml.pdf


Package source: kml_2.4.6.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): kml_2.4.6.1.tgz, r-oldrel (arm64): kml_2.4.6.1.tgz, r-release (x86_64): kml_2.4.6.1.tgz, r-oldrel (x86_64): kml_2.4.6.1.tgz
Old sources: kml archive

Reverse dependencies:

Reverse depends: kml3d
Reverse suggests: latrend


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