caviarpd
Cluster Analysis via Random Partition Distributions
Cluster analysis is performed using pairwise distance information and a random partition distribution. The method is implemented for two random partition distributions. It draws samples and then obtains and plots clustering estimates. An implementation of a selection algorithm is provided for the mass parameter of the partition distribution. Since pairwise distances are the principal input to this procedure, it is most comparable to the hierarchical and k-medoids clustering methods. The method is Dahl, Andros, Carter (2022+) <doi:10.1002/sam.11602>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.3.22 |
rolling linux/jammy R-4.5 | caviarpd_0.3.22.tar.gz |
360.0 KiB |
0.3.22 |
rolling linux/noble R-4.5 | caviarpd_0.3.22.tar.gz |
359.9 KiB |
0.3.22 |
rolling source/ R- | caviarpd_0.3.22.tar.gz |
2.0 MiB |
0.3.22 |
latest linux/jammy R-4.5 | caviarpd_0.3.22.tar.gz |
360.0 KiB |
0.3.22 |
latest linux/noble R-4.5 | caviarpd_0.3.22.tar.gz |
359.9 KiB |
0.3.22 |
latest source/ R- | caviarpd_0.3.22.tar.gz |
2.0 MiB |
0.3.22 |
2026-04-26 source/ R- | caviarpd_0.3.22.tar.gz |
2.0 MiB |
0.3.22 |
2026-04-23 source/ R- | caviarpd_0.3.22.tar.gz |
2.0 MiB |
0.3.22 |
2026-04-09 windows/windows R-4.5 | caviarpd_0.3.22.zip |
308.6 KiB |
0.3.16 |
2025-04-20 source/ R- | caviarpd_0.3.16.tar.gz |
2.8 MiB |
Dependencies (latest)
Suggests
- salso (>= 0.3.0)