BayesCPclust: A Bayesian Approach for Clustering Constant-Wise Change-Point Data

A Gibbs sampler algorithm was developed to estimate change points in constant-wise data sequences while performing clustering simultaneously. The algorithm is described in da Cruz, A. C. and de Souza, C. P. E "A Bayesian Approach for Clustering Constant-wise Change-point Data" <doi:10.48550/arXiv.2305.17631>.

Version:	0.1.0
Depends:	R (≥ 3.5.0)
Imports:	extraDistr, RcppAlgos, stats
Suggests:	testthat (≥ 3.0.0)
Published:	2025-01-29
Author:	Ana Carolina da Cruz [aut, cre]
Maintainer:	Ana Carolina da Cruz <adacruz at uwo.ca>
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	README
CRAN checks:	BayesCPclust results

Documentation:

Reference manual:

BayesCPclust.html , BayesCPclust.pdf

Downloads:

Package source:	BayesCPclust_0.1.0.tar.gz
Windows binaries:	r-devel: BayesCPclust_0.1.0.zip, r-release: BayesCPclust_0.1.0.zip, r-oldrel: BayesCPclust_0.1.0.zip
macOS binaries:	r-release (arm64): BayesCPclust_0.1.0.tgz, r-oldrel (arm64): BayesCPclust_0.1.0.tgz, r-release (x86_64): BayesCPclust_0.1.0.tgz, r-oldrel (x86_64): BayesCPclust_0.1.0.tgz

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