kml3d
K-Means for Joint Longitudinal Data
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.
- Version2.5.0
- R version≥ 2.10 methods,
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- kml3d citation info
- Last release10/23/2024
Documentation
Team
Christophe Genolini
Bruno Falissard
Show author detailsRolesContributorPatrice Kiener
Show author detailsRolesContributorJean-Baptiste Pingault
Show author detailsRolesContributor
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- Depends6 packages