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>.

Package details

AuthorDavid B. Dahl [aut, cre] (ORCID: <https://orcid.org/0000-0002-8173-1547>), R. Jacob Andros [aut] (ORCID: <https://orcid.org/0000-0002-1289-385X>), J. Brandon Carter [aut] (ORCID: <https://orcid.org/0000-0003-1687-0564>), Alex Crichton [ctb] (Rust crates: cfg-if, proc-macro2), Brendan Zabarauskas [ctb] (Rust crate: approx), David B. Dahl [ctb] (Rust crates: dahl-partition, dahl-salso, epa, roxido, roxido_macro), David Tolnay [ctb] (Rust crates: proc-macro2, quote, syn, unicode-ident), Jim Turner [ctb] (Rust crate: ndarray), Jorge Aparicio [ctb] (Rust crate: libm), Josh Stone [ctb] (Rust crate: autocfg), Mikhail Vorotilov [ctb] (Rust crate: roots), R. Janis Goldschmidt [ctb] (Rust crate: matrixmultiply), Sean McArthur [ctb] (Rust crate: num_cpus), Stefan Lankes [ctb] (Rust crate: hermit-abi), The Cranelift Project Developers [ctb] (Rust crate: wasi), The CryptoCorrosion Contributors [ctb] (Rust crates: ppv-lite86, rand_chacha), The Rand Project Developers [ctb] (Rust crates: getrandom, rand, rand_chacha, rand_core, rand_distr, rand_pcg), The Rust Project Developers [ctb] (Rust crates: libc, num-complex, num-integer, num-traits, rand, rand_chacha, rand_core), Ulrik Sverdrup "bluss" [ctb] (Rust crate: ndarray), bluss [ctb] (Rust crates: matrixmultiply, rawpointer)
MaintainerDavid B. Dahl <dahl@stat.byu.edu>
LicenseMIT + file LICENSE | Apache License 2.0
Version0.3.21
URL https://github.com/dbdahl/caviarpd-package
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("caviarpd")

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caviarpd documentation built on Nov. 5, 2025, 6:30 p.m.