MoEClust (1.2.3)

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Gaussian Parsimonious Clustering Models with Covariates and a Noise Component.

https://cran.r-project.org/package=MoEClust
http://cran.r-project.org/web/packages/MoEClust

Clustering via parsimonious Gaussian Mixtures of Experts using the MoEClust models introduced by Murphy and Murphy (2018) . 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.

Maintainer: Keefe Murphy
Author(s): Keefe Murphy [aut, cre], Thomas Brendan Murphy [ctb]

License: GPL (>= 2)

Uses: lattice, matrixStats, mclust, mvnfast, nnet, vcd, cluster, geometry, knitr, clustMD, rmarkdown

Released 4 months ago.


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