kml3d 2.4.2

K-Means for Joint Longitudinal Data

Released Aug 8, 2017 by Christophe Genolini

This package cannot yet be used with Renjin it depends on other packages which are not available: rgl 0.99.16, longitudinalData 2.4.1, and kml 2.4.1


kml 2.4.1 rgl 0.99.16 longitudinalData 2.4.1 misc3d 0.8-4 clv 0.3-2.1

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.