HDclust
Clustering High Dimensional Data with Hidden Markov Model on Variable Blocks
Clustering of high dimensional data with Hidden Markov Model on Variable Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin Lin and Jia Li (2017) <https://jmlr.org/papers/v18/16-342.html>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.4 |
rolling source/ R- | HDclust_1.0.4.tar.gz |
903.4 KiB |
1.0.4 |
rolling linux/jammy R-4.5 | HDclust_1.0.4.tar.gz |
1.1 MiB |
1.0.4 |
rolling linux/noble R-4.5 | HDclust_1.0.4.tar.gz |
1.1 MiB |
1.0.4 |
latest source/ R- | HDclust_1.0.4.tar.gz |
903.4 KiB |
1.0.4 |
latest linux/jammy R-4.5 | HDclust_1.0.4.tar.gz |
1.1 MiB |
1.0.4 |
latest linux/noble R-4.5 | HDclust_1.0.4.tar.gz |
1.1 MiB |
1.0.4 |
2026-04-23 source/ R- | HDclust_1.0.4.tar.gz |
903.4 KiB |
1.0.4 |
2026-04-09 windows/windows R-4.5 | HDclust_1.0.4.zip |
1.4 MiB |
1.0.4 |
2025-04-20 source/ R- | HDclust_1.0.4.tar.gz |
903.4 KiB |