bgms: Bayesian Analysis of 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/osf.io/ukwrf>.

Version: 0.1.3
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 1.0.7), Rdpack, methods
LinkingTo: Rcpp, RcppProgress
Suggests: knitr, qgraph, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-02-25
Author: Maarten Marsman ORCID iD [aut, cre], Karoline Huth ORCID iD [ctb], Nikola Sekulovski ORCID iD [ctb], Don van den Bergh ORCID iD [ctb]
Maintainer: Maarten Marsman <m.marsman at uva.nl>
BugReports: https://github.com/MaartenMarsman/bgms/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://maartenmarsman.github.io/bgms/
NeedsCompilation: yes
Citation: bgms citation info
Materials: README NEWS
CRAN checks: bgms results

Documentation:

Reference manual: bgms.pdf
Vignettes: Introducing bgms

Downloads:

Package source: bgms_0.1.3.tar.gz
Windows binaries: r-devel: bgms_0.1.3.zip, r-release: bgms_0.1.3.zip, r-oldrel: bgms_0.1.3.zip
macOS binaries: r-release (arm64): bgms_0.1.3.tgz, r-oldrel (arm64): bgms_0.1.3.tgz, r-release (x86_64): bgms_0.1.3.tgz
Old sources: bgms archive

Reverse dependencies:

Reverse imports: easybgm

Linking:

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