Package: BayesCPclust 0.1.0
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Ana Carolina da Cruz
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>.
Authors:
BayesCPclust_0.1.0.tar.gz
BayesCPclust_0.1.0.tar.gz(r-4.5-noble)BayesCPclust_0.1.0.tar.gz(r-4.4-noble)
BayesCPclust_0.1.0.tgz(r-4.4-emscripten)BayesCPclust_0.1.0.tgz(r-4.3-emscripten)
BayesCPclust.pdf |BayesCPclust.html✨
BayesCPclust/json (API)
# Install 'BayesCPclust' in R: |
install.packages('BayesCPclust', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 22 days agofrom:8713ec988e. Checks:2 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Jan 29 2025 |
R-4.5-linux | OK | Jan 29 2025 |
Exports:full_condgibbs_alglogsumexpModepkpossigma2npostalpha0postalphakpostKpostK_mkpostmkqn0qn0_mkqnjrun_gibbsupdate_lambda
Dependencies:cpp11extraDistrgmpRcppRcppAlgos