CRAN/E | MoEClust

MoEClust

Gaussian Parsimonious Clustering Models with Covariates and a Noise Component

Installation

About

Clustering via parsimonious Gaussian Mixtures of Experts using the MoEClust models introduced by Murphy and Murphy (2020) doi:10.1007/s11634-019-00373-8. This package fits finite Gaussian mixture models with a formula interface for supplying gating and/or expert network covariates using a range of parsimonious covariance parameterisations from the GPCM family via the EM/CEM algorithm. Visualisation of the results of such models using generalised pairs plots and the inclusion of an additional noise component is also facilitated. A greedy forward stepwise search algorithm is provided for identifying the optimal model in terms of the number of components, the GPCM covariance parameterisation, and the subsets of gating/expert network covariates.

Citation MoEClust citation info
cran.r-project.org/package=MoEClust
Bug report File report

Key Metrics

Version 1.5.2
R ≥ 4.0.0
Published 2023-12-11 108 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks MoEClust results

Downloads

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Maintainer

Maintainer

Keefe Murphy

keefe.murphy@mu.ie

Authors

Keefe Murphy

aut / cre

Thomas Brendan Murphy

ctb

Material

README
NEWS
Reference manual
Package source

In Views

Cluster

Vignettes

MoEClust

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

MoEClust archive

Depends

R ≥ 4.0.0

Imports

lattice ≥ 0.12
matrixStats ≥ 1.0.0
mclust ≥ 5.4
mvnfast
nnet ≥ 7.3-0
vcd

Suggests

cluster ≥ 1.4.0
clustMD ≥ 1.2.1
geometry ≥ 0.4.0
knitr
rmarkdown
snow