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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.2.0 |
rolling linux/jammy R-4.5 | mixture_2.2.0.tar.gz |
683.2 KiB |
2.2.0 |
rolling linux/noble R-4.5 | mixture_2.2.0.tar.gz |
696.7 KiB |
2.2.0 |
rolling source/ R- | mixture_2.2.0.tar.gz |
210.4 KiB |
2.2.0 |
latest linux/jammy R-4.5 | mixture_2.2.0.tar.gz |
683.2 KiB |
2.2.0 |
latest linux/noble R-4.5 | mixture_2.2.0.tar.gz |
696.7 KiB |
2.2.0 |
latest source/ R- | mixture_2.2.0.tar.gz |
210.4 KiB |
2.2.0 |
2026-04-26 source/ R- | mixture_2.2.0.tar.gz |
210.4 KiB |
2.2.0 |
2026-04-23 source/ R- | mixture_2.2.0.tar.gz |
210.4 KiB |
2.2.0 |
2026-04-09 windows/windows R-4.5 | mixture_2.2.0.zip |
1.0 MiB |
2.1.1 |
2025-04-20 source/ R- | mixture_2.1.1.tar.gz |
209.9 KiB |