RMixtComp
Mixture Models with Heterogeneous and (Partially) Missing Data
Mixture Composer (Biernacki (2015) <https://inria.hal.science/hal-01253393v1>) is a project to perform clustering using mixture models with heterogeneous data and partially missing data. Mixture models are fitted using a SEM algorithm. It includes 8 models for real, categorical, counting, functional and ranking data.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
4.1.5 |
rolling linux/jammy R-4.5 | RMixtComp_4.1.5.tar.gz |
1.1 MiB |
4.1.5 |
rolling linux/noble R-4.5 | RMixtComp_4.1.5.tar.gz |
1.1 MiB |
4.1.5 |
rolling source/ R- | RMixtComp_4.1.5.tar.gz |
1.2 MiB |
4.1.5 |
latest linux/jammy R-4.5 | RMixtComp_4.1.5.tar.gz |
1.1 MiB |
4.1.5 |
latest linux/noble R-4.5 | RMixtComp_4.1.5.tar.gz |
1.1 MiB |
4.1.5 |
latest source/ R- | RMixtComp_4.1.5.tar.gz |
1.2 MiB |
4.1.5 |
2026-04-26 source/ R- | RMixtComp_4.1.5.tar.gz |
1.2 MiB |
4.1.5 |
2026-04-23 source/ R- | RMixtComp_4.1.5.tar.gz |
1.2 MiB |
4.1.5 |
2026-04-09 windows/windows R-4.5 | RMixtComp_4.1.5.zip |
1.1 MiB |
4.1.4 |
2025-04-20 source/ R- | RMixtComp_4.1.4.tar.gz |
1.2 MiB |