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 plot 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.

Version:	0.2.11
Depends:	R (≥ 3.5.0), salso (≥ 0.2.20)
Imports:	cluster (≥ 2.1.2)
Published:	2021-06-04
Author:	David B. Dahl [aut, cre], Brandon Carter [aut], Jacob Andros [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

Downloads:

Reference manual:	caviarpd.pdf
Package source:	caviarpd_0.2.11.tar.gz
Windows binaries:	r-devel: caviarpd_0.2.11.zip, r-devel-UCRT: caviarpd_0.2.11.zip, r-release: caviarpd_0.2.11.zip, r-oldrel: caviarpd_0.2.11.zip
macOS binaries:	r-release (arm64): caviarpd_0.2.11.tgz, r-release (x86_64): caviarpd_0.2.11.tgz, r-oldrel: caviarpd_0.2.11.tgz

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