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.

Version:	2.4.1
Depends:	methods, clv, longitudinalData (≥ 2.4)
Published:	2016-02-16
Author:	Christophe Genolini [cre, aut], Bruno Falissard [ctb]
Maintainer:	Christophe Genolini <christophe.genolini at u-paris10.fr>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	http:www.r-project.org
NeedsCompilation:	yes
Citation:	kml citation info
In views:	Cluster
CRAN checks:	kml results

Documentation:

Reference manual:

kml.pdf

Downloads:

Package source:	kml_2.4.1.tar.gz
Windows binaries:	r-devel: kml_2.4.1.zip, r-release: kml_2.4.1.zip, r-oldrel: kml_2.4.1.zip
macOS binaries:	r-release (arm64): kml_2.4.1.tgz, r-oldrel (arm64): kml_2.4.1.tgz, r-release (x86_64): kml_2.4.1.tgz, r-oldrel (x86_64): kml_2.4.1.tgz
Old sources:	kml archive

Reverse dependencies:

Reverse depends:	kml3d, kmlShape
Reverse imports:	akmedoids
Reverse suggests:	latrend

Linking:

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