ssgraph: Bayesian Graph Structure Learning using Spike-and-Slab Priors

Bayesian estimation for undirected graphical models using spike-and-slab priors. The package handles continuous, discrete, and mixed data.

Version: 1.13
Depends: BDgraph (≥ 2.58)
Suggests: skimr, knitr, rmarkdown
Published: 2022-05-09
Author: Reza Mohammadi ORCID iD [aut, cre]
Maintainer: Reza Mohammadi <a.mohammadi at uva.nl>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.uva.nl/profile/a.mohammadi
NeedsCompilation: yes
Citation: ssgraph citation info
Materials: README NEWS
In views: Bayesian, HighPerformanceComputing, MachineLearning
CRAN checks: ssgraph results

Documentation:

Reference manual: ssgraph.pdf
Vignettes: ssgraph with simple sxample

Downloads:

Package source: ssgraph_1.13.tar.gz
Windows binaries: r-devel: ssgraph_1.13.zip, r-release: ssgraph_1.13.zip, r-oldrel: ssgraph_1.13.zip
macOS binaries: r-release (arm64): ssgraph_1.13.tgz, r-oldrel (arm64): ssgraph_1.13.tgz, r-release (x86_64): ssgraph_1.13.tgz, r-oldrel (x86_64): ssgraph_1.13.tgz
Old sources: ssgraph archive

Reverse dependencies:

Reverse suggests: BDgraph

Linking:

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