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