funHDDC
Univariate and Multivariate Model-Based Clustering in Group-Specific Functional Subspaces
The funHDDC algorithm allows to cluster functional univariate (Bouveyron and Jacques, 2011, <doi:10.1007/s11634-011-0095-6>) or multivariate data (Schmutz et al., 2018) by modeling each group within a specific functional subspace.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.3.1.1 |
rolling linux/jammy R-4.5 | funHDDC_2.3.1.1.tar.gz |
499.7 KiB |
2.3.1.1 |
rolling linux/noble R-4.5 | funHDDC_2.3.1.1.tar.gz |
499.5 KiB |
2.3.1.1 |
rolling source/ R- | funHDDC_2.3.1.1.tar.gz |
389.7 KiB |
2.3.1.1 |
latest linux/jammy R-4.5 | funHDDC_2.3.1.1.tar.gz |
499.7 KiB |
2.3.1.1 |
latest linux/noble R-4.5 | funHDDC_2.3.1.1.tar.gz |
499.5 KiB |
2.3.1.1 |
latest source/ R- | funHDDC_2.3.1.1.tar.gz |
389.7 KiB |
2.3.1.1 |
2026-04-23 source/ R- | funHDDC_2.3.1.1.tar.gz |
0 B |