An implementation of k-means specifically design to cluster joint trajectories (longitudinal data on several variable-trajectories). Like 'kml', 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. In addition, the 3D graph representing the mean joint-trajectories of each cluster can be exported through LaTeX in a 3D dynamic rotating PDF graph.
| Version: | 2.4.2 |
| Depends: | methods, clv, rgl, misc3d, longitudinalData (≥ 2.4.1), kml (≥ 2.4.1) |
| Published: | 2017-08-08 |
| Author: | Christophe Genolini [cre, aut], Bruno Falissard [ctb], Jean-Baptiste Pingault [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: | no |
| Citation: | kml3d citation info |
| CRAN checks: | kml3d results |
| Reference manual: | kml3d.pdf |
| Package source: | kml3d_2.4.2.tar.gz |
| Windows binaries: | r-devel: kml3d_2.4.2.zip, r-release: kml3d_2.4.2.zip, r-oldrel: kml3d_2.4.2.zip |
| macOS binaries: | r-release: kml3d_2.4.2.tgz, r-oldrel: kml3d_2.4.2.tgz |
| Old sources: | kml3d archive |
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