This package allows to fit, according to the expectation-conditional maximization algorithm, the 14 parsimonious mixtures of multivariate contaminated normal distributions, with eigen-decomposed scale matrices, introduced by Punzo and McNicholas (2016). Model-based clustering and classification scenarios are implemented. Likelihood-based model selection criteria can be adopted to select the parsimonious model and the number of groups.
Antonio Punzo, Angelo Mazza, Paul D. McNicholas
Maintainer: Angelo Mazza <[email protected]>
Punzo A., Mazza A. and McNicholas P. D. (2018). ContaminatedMixt: An R Package for Fitting Parsimonious Mixtures of Multivariate Contaminated Normal Distributions. Journal of Statistical Software, 85(10), 1–25.
Punzo A. and McNicholas P. D. (2016). Parsimonious mixtures of multivariate contaminated normal distributions. Biometrical Journal, 58(6), 1506–1537.
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