ContaminatedMixt-package: ContaminatedMixt - Parsimonious Mixtures of Contaminated...

In ContaminatedMixt: Clustering and Classification with the Contaminated Normal

ContaminatedMixt - Parsimonious Mixtures of Contaminated Normal Distributions

Description

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.

Details

Package:	ContaminatedMixt
Type:	Package
Version:	1.1
Date:	2016-09-02
License:	GNU-2

Author(s)

Antonio Punzo, Angelo Mazza, Paul D. McNicholas

Maintainer: Angelo Mazza <[e-mail]>

References

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.

See Also

CNmixt

ContaminatedMixt documentation built on May 31, 2023, 6:44 p.m.