mixture
Mixture Models for Clustering and Classification
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).
- Version2.1.1
- R version≥ 3.5.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Celeux and Govaert (1995)
- Browne and McNicholas (2014)
- Browne and McNicholas (2015)
- Last release01/30/2024
Documentation
Team
Paul D. McNicholas
Ryan P. Browne
Show author detailsRolesAuthorNik Pocuca
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- Depends1 package
- Imports1 package
- Linking To4 packages
- Reverse Imports4 packages