BDgraph: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

Statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi and Wit (2019) <doi:10.18637/jss.v089.i03>.

Version: 2.62
Imports: igraph
Published: 2019-12-05
Author: Reza Mohammadi [aut, cre] <https://orcid.org/0000-0001-9538-0648>, Ernst Wit [aut] <https://orcid.org/0000-0002-3671-9610>, Adrian Dobra [ctb]
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: BDgraph citation info
Materials: NEWS
In views: Bayesian, HighPerformanceComputing, MachineLearning, gR
CRAN checks: BDgraph results

Downloads:

Reference manual: BDgraph.pdf
Vignettes: An Introduction to the BDgraph Package for Bayesian Graphical Models
Package source: BDgraph_2.62.tar.gz
Windows binaries: r-devel: BDgraph_2.62.zip, r-release: BDgraph_2.62.zip, r-oldrel: BDgraph_2.62.zip
macOS binaries: r-release: BDgraph_2.62.tgz, r-oldrel: BDgraph_2.62.tgz
Old sources: BDgraph archive

Reverse dependencies:

Reverse depends: ssgraph
Reverse imports: bmixture, bootnet, qgraph
Reverse suggests: BayesSUR

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