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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) <doi:10.1016/0031-3203(94)00125-6>, Browne and McNicholas (2014) <doi:10.1007/s11634-013-0139-1>, Browne and McNicholas (2015) <doi:10.1002/cjs.11246>.
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Package details |
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| Author | Nik Pocuca [aut] (<https://orcid.org/0000-0001-8365-0751>), Ryan P. Browne [aut] (<https://orcid.org/0000-0003-4543-0218>), Paul D. McNicholas [aut, cre] (<https://orcid.org/0000-0002-2482-523X>) |
| Maintainer | Paul D. McNicholas <mcnicholas@math.mcmaster.ca> |
| License | GPL (>= 2) |
| Version | 2.1.1 |
| Package repository | View on CRAN |
| Installation |
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