Package: MoEClust
Type: Package
Date: 2019-12-11
Title: Gaussian Parsimonious Clustering Models with Covariates and a
        Noise Component
Version: 1.2.4
Authors@R: c(person("Keefe", "Murphy", email = "keefe.murphy@ucd.ie", role = c("aut", "cre")),
           person("Thomas Brendan", "Murphy", email = "brendan.murphy@ucd.ie", role = "ctb"))
Description: Clustering via parsimonious Gaussian Mixtures of Experts using the MoEClust models introduced by Murphy and Murphy (2019) <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.
Depends: R (>= 3.3.0)
License: GPL (>= 2)
Encoding: UTF-8
URL: https://cran.r-project.org/package=MoEClust
BugReports: https://github.com/Keefe-Murphy/MoEClust
LazyData: true
Imports: lattice, matrixStats, mclust (>= 5.1), mvnfast, nnet, vcd
Suggests: cluster, clustMD, geometry, knitr, parallel, rmarkdown
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-12-11 01:57:30 UTC; Keefe
Author: Keefe Murphy [aut, cre],
  Thomas Brendan Murphy [ctb]
Maintainer: Keefe Murphy <keefe.murphy@ucd.ie>
Repository: CRAN
Date/Publication: 2019-12-11 05:50:02 UTC
