mixture: Mixture Models for Clustering and Classification
Nik Pocuca, Ryan P. Browne, Paul D. McNicholas, Alexa A. Sochaniwsky · 2013
An implementation of 14 parsimonious mixture models for model-based clustering or model-based classification. Gaussian, Student's t, generalized hyperbolic, variance-gamma or skew-t mixtures are available. All approaches work with missing data. Celeux and Govaert (1995) , Browne and McNicholas (2014) , Browne and McNicholas (2015) .