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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: 1.15
Depends: BDgraph (≥ 2.58)
Suggests: skimr, knitr, rmarkdown
Published: 2022-12-24
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_1.15.tar.gz
Windows binaries: r-devel: ssgraph_1.15.zip, r-release: ssgraph_1.15.zip, r-oldrel: ssgraph_1.15.zip
macOS binaries: r-release (arm64): ssgraph_1.15.tgz, r-oldrel (arm64): ssgraph_1.15.tgz, r-release (x86_64): ssgraph_1.15.tgz, r-oldrel (x86_64): ssgraph_1.15.tgz
Old sources: ssgraph archive

Reverse dependencies:

Reverse suggests: BDgraph

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ssgraph to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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