kml3d (2.4.2)

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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.

Maintainer: Christophe Genolini
Author(s): Christophe Genolini [cre, aut], Bruno Falissard [ctb], Jean-Baptiste Pingault [ctb]

License: GPL (>= 2)

Uses: clv, misc3d, rgl

Released over 2 years ago.

12 previous versions



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