kml3d: K-means for joint Longitudinal data

KmL3D is an implementation of k-means specificaly design to deal with joint trajectories (longitudinal data on several variable-trajectories). It provide facilities to deal with missing value, compute several quality criterion (Calinski and Harabatz, Ray and Turie, Davies and Bouldin) and propose a graphical interphace for chosing the 'best' number of clusters.

Version: 2.0
Depends: methods, clv, rgl, misc3d, longitudinalData, kml
Published: 2012-03-28
Author: Christophe Genolini
Maintainer: Christophe Genolini <genolini at u-paris10.fr>
License: GPL (≥ 2)
URL: http:www.r-project.org
In views: Cluster
CRAN checks: kml3d results

Downloads:

Package source: kml3d_2.0.tar.gz
MacOS X binary: kml3d_2.0.tgz
Windows binary: kml3d_2.0.zip
Reference manual: kml3d.pdf
Old sources: kml3d archive