kml: K-Means for Longitudinal Data

An implementation of k-means specifically design to cluster longitudinal data. 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.

AuthorChristophe Genolini [cre, aut], Bruno Falissard [ctb]
Date of publication2016-02-16 23:12:45
MaintainerChristophe Genolini <christophe.genolini@u-paris10.fr>
LicenseGPL (>= 2)
Version2.4.1
http:www.r-project.org

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Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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