MoEClust: Parsimonious Model-Based Clustering with Covariates

Clustering via parsimonious Mixtures of Experts using the MoEClust models introduced by Murphy and Murphy (2017) <arXiv:1711.05632>. This package fits finite Gaussian mixture models with gating and expert network covariates using parsimonious covariance parameterisations from 'mclust' via the EM algorithm. Visualisation of the results of such models using generalised pairs plots is also facilitated.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: grid, lattice, matrixStats, mclust (≥ 5.1), mvnfast, nnet, vcd
Suggests: cluster, geometry, knitr, rmarkdown
Published: 2017-11-28
Author: Keefe Murphy [aut, cre], Thomas Brendan Murphy [ctb]
Maintainer: Keefe Murphy <keefe.murphy at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: MoEClust citation info
Materials: README NEWS
CRAN checks: MoEClust results


Reference manual: MoEClust.pdf
Vignettes: MoEClust
Package source: MoEClust_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: MoEClust_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: MoEClust_1.0.0.tgz


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