MoEClust
swMATH35305CRANMoEClustMaRDI QIDQ47014
Gaussian Parsimonious Clustering Models with Covariates and a Noise Component
Last update: 11 December 2023
Copyright license: GNU General Public License
Software version identifier: 1.5.1, 1.0.0, 1.1.0, 1.2.0, 1.2.1, 1.2.2, 1.2.3, 1.2.4, 1.3.0, 1.3.1, 1.3.2, 1.3.3, 1.4.0, 1.4.1, 1.4.2, 1.5.0, 1.5.2
Source code repository: https://github.com/cran/MoEClust
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.
