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 currently under peer review at a journal.
| Version: |
0.2.17 |
| Depends: |
R (≥ 4.0.0), salso (≥ 0.2.20) |
| Imports: |
cluster (≥ 2.1.2) |
| Published: |
2021-08-13 |
| Author: |
David B. Dahl 
[aut, cre],
Jacob Andros
[aut],
J. Brandon Carter
[aut] |
| Maintainer: |
David B. Dahl <dahl at stat.byu.edu> |
| License: |
MIT + file LICENSE | Apache License 2.0 |
| NeedsCompilation: |
yes |
| SystemRequirements: |
Cargo (>= 1.51) for installation from sources: see
INSTALL file |
| Materials: |
NEWS INSTALL |
| CRAN checks: |
caviarpd results |
Documentation:
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