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

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) <https://doi:10.1214/14-BA889> and Mohammadi et al. (2017) <https://doi:10.1111/rssc.12171>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.

Version:	2.47
Depends:	R (≥ 3.0.0), Matrix, igraph, ssgraph
Published:	2018-04-25
Author:	Reza Mohammadi and Ernst Wit
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:	gR
CRAN checks:	BDgraph results

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