BGGM: Bayesian Gaussian Graphical Models

Fit Bayesian Gaussian graphical models. The methods are separated into two Bayesian approaches for inference: hypothesis testing and estimation. There are extensions for confirmatory hypothesis testing, comparing Gaussian graphical models, and node wise predictability. These methods were recently introduced in the Gaussian graphical model literature, including Williams (2019) <doi:10.31234/>, Williams and Mulder (2019) <doi:10.31234/>, Williams, Rast, Pericchi, and Mulder (2019) <doi:10.31234/>.

Version: 2.1.3
Depends: R (≥ 4.3.0)
Imports: BFpack (≥ 1.2.3), GGally (≥ 1.4.0), ggplot2 (≥ 3.2.1), ggridges (≥ 0.5.1), grDevices, MASS (≥ 7.3-51.5), methods, mvnfast (≥ 0.2.5), network (≥ 1.15), reshape (≥ 0.8.8), Rcpp (≥, Rdpack (≥ 0.11-1), sna (≥ 2.5), stats, utils
LinkingTo: Rcpp, RcppArmadillo, RcppDist, RcppProgress
Suggests: abind (≥ 1.4-5), assortnet (≥ 0.12), networktools (≥ 1.3.0), mice (≥ 3.8.0), psych, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-07-05
DOI: 10.32614/CRAN.package.BGGM
Author: Donald Williams [aut], Joris Mulder [aut], Philippe Rast [aut, cre]
Maintainer: Philippe Rast < at>
License: GPL-2
NeedsCompilation: yes
Citation: BGGM citation info
Materials: NEWS
CRAN checks: BGGM results


Reference manual: BGGM.pdf
Vignettes: Controlling for Variables
Three Ways to Test the Same Hypothesis
In Tandem: Confirmatory and Exploratory Testing
MCMC Diagnostics
Network Plots
Custom Network Statistics
Custom Network Comparisons
Predictability: Binary, Ordinal, and Continuous
Testing Sums
Graphical VAR


Package source: BGGM_2.1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BGGM_2.1.3.tgz, r-oldrel (arm64): BGGM_2.1.3.tgz, r-release (x86_64): BGGM_2.1.3.tgz, r-oldrel (x86_64): BGGM_2.1.3.tgz
Old sources: BGGM archive

Reverse dependencies:

Reverse imports: easybgm


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