dmbc: Model Based Clustering of Binary Dissimilarity Measurements

Functions for fitting a Bayesian model for grouping binary dissimilarity matrices in homogeneous clusters. Currently, it includes methods only for binary data.

Version: 0.3.0
Depends: methods, R (≥ 3.6.0), stats, utils
Imports: abind, bayesplot (≥ 1.7.0), coda (≥ 0.19-3), ggplot2 (≥ 3.2.1), ggrepel (≥ 0.8.1), graphics, MCMCpack (≥ 1.4-4), modeltools (≥ 0.2-22), parallel (≥ 3.6.1), pcaPP (≥ 1.9-73), robustbase (≥ 0.93-5), stats4 (≥ 3.6.0), tools
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: knitr, mcmcplots, rlecuyer, testthat
Published: 2020-06-12
Author: Sergio Venturini [aut, cre], Raffaella Piccarreta [aut]
Maintainer: Sergio Venturini <sergio.venturini at unito.it>
BugReports: https://github.com/sergioventurini/dmbc/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: dmbc results

Downloads:

Reference manual: dmbc.pdf
Package source: dmbc_0.3.0.tar.gz
Windows binaries: r-devel: dmbc_0.3.0.zip, r-release: dmbc_0.3.0.zip, r-oldrel: dmbc_0.3.0.zip
macOS binaries: r-release: dmbc_0.3.0.tgz, r-oldrel: dmbc_0.3.0.tgz

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