SDisc: Integrated methodology for the identification of homogeneous subtypes in data

Tools and methods to identify homogeneous subtypes in data by cluster analysis; includes methods for data pre-processing, repeated cluster analysis, model selection, model reliability and reproducibility assessment, subtype characterization and validation.

Version: 1.24
Depends: R (≥ 2.12.1), mclust, stats, utils, RColorBrewer, abind, xtable, digest, e1071, snow, SparseM
Published: 2011-11-02
Author: Fabrice Colas
Maintainer: Fabrice Colas <sdisc at grano-salis.fr>
License: BSD
URL: http://grano-salis.fr/sdisc/
In views: Cluster
CRAN checks: SDisc results

Downloads:

Package source: SDisc_1.24.tar.gz
MacOS X binary: SDisc_1.24.tgz
Windows binary: SDisc_1.24.zip
Reference manual: SDisc.pdf
Vignettes: SDisc-vignette
Old sources: SDisc archive