bgms: Bayesian Variable Selection for Networks of Binary and/or Ordinal Variables

Bayesian variable selection methods for analyzing the structure of a Markov Random Field model for a network of binary and/or ordinal variables. Details of the implemented methods can be found in: Marsman and Haslbeck (2023) <doi:10.31234/>.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 1.0.7), Rdpack, methods
LinkingTo: Rcpp, RcppProgress
Suggests: knitr, qgraph, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-09-01
Author: Maarten Marsman ORCID iD [aut, cre], Nikola Sekulovski ORCID iD [ctb], Don van den Bergh ORCID iD [ctb]
Maintainer: Maarten Marsman <m.marsman at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: bgms citation info
Materials: README NEWS
CRAN checks: bgms results


Reference manual: bgms.pdf
Vignettes: Introducing bgms


Package source: bgms_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bgms_0.1.1.tgz, r-oldrel (arm64): bgms_0.1.1.tgz, r-release (x86_64): bgms_0.1.1.tgz, r-oldrel (x86_64): bgms_0.1.1.tgz
Old sources: bgms archive


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