Depends: R (>= 3.0.0), network, huge, Matrix
The main function is 'bdgraph' which is a birth-death MCMC
Packaged: 2013-04-21 20:38:42 UTC; Administrator

Author: Reza Mohammadi (<https://orcid.org/0000-0001-9538-0648>) and Ernst Wit

Author: Reza Mohammadi <https://orcid.org/0000-0001-9538-0648> and Ernst Wit <https://orcid.org/0000-0002-3671-9610>
Description: 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++.
Depends: R (>= 3.0.0), Matrix, igraph, ssgraph

Author: Reza Mohammadi [aut, cre] <https://orcid.org/0000-0001-9538-0648>,

Title: Graph determination based on BD-MCMC algorithm
Depends: R (>= 3.0.0), igraph, Matrix, huge

Description: 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++.

Description: 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>, Letac et al. (2018) <arXiv:1706.04416>, Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>, Mohammadi et al. (2017) <doi:10.1111/rssc.12171>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.