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/osf.io/ukwrf>.

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 [aut, cre], Nikola Sekulovski [ctb], Don van den Bergh [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_0.1.1.tar.gz
Windows binaries:	r-devel: bgms_0.1.1.zip, r-release: bgms_0.1.1.zip, r-oldrel: bgms_0.1.1.zip
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

Linking:

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