kml3d: K-Means for Joint Longitudinal Data
Version 2.4.1

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.

Package details

AuthorChristophe Genolini [cre, aut], Bruno Falissard [ctb], Jean-Baptiste Pingault [ctb]
Date of publication2016-02-16 16:15:26
MaintainerChristophe Genolini <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the kml3d package in your browser

Any scripts or data that you put into this service are public.

kml3d documentation built on April 14, 2017, 10:19 a.m.