EMCluster: EM Algorithm for Model-Based Clustering of Finite Mixture Gaussian Distribution

EM algorithms and several efficient initialization methods for model-based clustering of finite mixture Gaussian distribution with unstructured dispersion in both of unsupervised and semi-supervised learning.

Version: 0.2-10
Depends: R (≥ 3.0.1), MASS, Matrix
Enhances: PPtree, RColorBrewer
Published: 2018-02-01
Author: Wei-Chen Chen [aut, cre], Ranjan Maitra [aut], Volodymyr Melnykov [ctb], Dan Nettleton [ctb], David Faden [ctb], Rouben Rostamian [ctb], R Core team [ctb] (some functions are modified from the R source code)
Maintainer: Wei-Chen Chen <wccsnow at gmail.com>
BugReports: https://github.com/snoweye/EMCluster/issues
License: Mozilla Public License 2.0
URL: https://github.com/snoweye/EMCluster
NeedsCompilation: yes
Citation: EMCluster citation info
Materials: README ChangeLog INSTALL
In views: Cluster
CRAN checks: EMCluster results


Reference manual: EMCluster.pdf
Vignettes: EMCluster-guide
Package source: EMCluster_0.2-10.tar.gz
Windows binaries: r-devel: EMCluster_0.2-10.zip, r-release: EMCluster_0.2-10.zip, r-oldrel: EMCluster_0.2-10.zip
OS X binaries: r-release: EMCluster_0.2-10.tgz, r-oldrel: EMCluster_0.2-10.tgz
Old sources: EMCluster archive

Reverse dependencies:

Reverse imports: MixfMRI
Reverse suggests: cubfits, fdapace
Reverse enhances: pbdDEMO


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