Provides 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 et al. (2017) <doi:10.1111/rssc.12171>, and Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.
Version: | 2.53 |
Imports: | Matrix, igraph |
Published: | 2018-11-14 |
Author: | Reza Mohammadi [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: | BDgraph citation info |
Materials: | NEWS |
In views: | Bayesian, HighPerformanceComputing, gR |
CRAN checks: | BDgraph results |
Reference manual: | BDgraph.pdf |
Vignettes: |
BDgraph: An R Package for Bayesian Structure Learning in Graphical Models |
Package source: | BDgraph_2.53.tar.gz |
Windows binaries: | r-devel: BDgraph_2.53.zip, r-release: BDgraph_2.53.zip, r-oldrel: BDgraph_2.53.zip |
OS X binaries: | r-release: BDgraph_2.53.tgz, r-oldrel: BDgraph_2.53.tgz |
Old sources: | BDgraph archive |
Reverse depends: | ssgraph |
Reverse imports: | bmixture, bootnet, qgraph |
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