easybgm: Extracting and Visualizing Bayesian Graphical Models

Fit and visualize the results of a Bayesian analysis of networks commonly found in psychology. The package supports fitting cross-sectional network models fitted using the packages 'BDgraph', 'bgms' and 'BGGM'. The package provides the parameter estimates, posterior inclusion probabilities, inclusion Bayes factor, and the posterior density of the parameters. In addition, for 'BDgraph' and 'bgms' it allows to assess the posterior structure space. Furthermore, the package comes with an extensive suite for visualizing results.

Version: 0.1.2
Imports: BDgraph, BGGM, bgms (≥ 0.1.3), dplyr, ggplot2, HDInterval, igraph, qgraph
Suggests: testthat (≥ 3.0.0), vdiffr
Published: 2024-03-13
DOI: 10.32614/CRAN.package.easybgm
Author: Karoline Huth ORCID iD [aut, cre], Sara Keetelaar [ctb]
Maintainer: Karoline Huth <k.huth at uva.nl>
BugReports: https://github.com/KarolineHuth/easybgm/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/KarolineHuth/easybgm
NeedsCompilation: no
Materials: README
CRAN checks: easybgm results


Reference manual: easybgm.pdf


Package source: easybgm_0.1.2.tar.gz
Windows binaries: r-devel: easybgm_0.1.2.zip, r-release: easybgm_0.1.2.zip, r-oldrel: easybgm_0.1.2.zip
macOS binaries: r-release (arm64): easybgm_0.1.2.tgz, r-oldrel (arm64): easybgm_0.1.2.tgz, r-release (x86_64): easybgm_0.1.2.tgz, r-oldrel (x86_64): easybgm_0.1.2.tgz
Old sources: easybgm archive


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