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CRAN: Package kml3d

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.

Version: 2.5.0 Depends: R (≥ 2.10), methods, clv, rgl, misc3d, longitudinalData, kml Published: 2024-10-23 DOI: 10.32614/CRAN.package.kml3d Author: Christophe Genolini [cre, aut], Bruno Falissard [ctb], Patrice Kiener [ctb], Jean-Baptiste Pingault [ctb] Maintainer: Christophe Genolini <christophe.genolini at free.fr> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] NeedsCompilation: no Citation: kml3d citation info Materials: NEWS CRAN checks: kml3d results Documentation: Downloads: Linking:

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