BDgraph: Bayesian Structure Learning of Graphs in R

We introduce an R package BDgraph which performs Bayesian structure learning in high-dimensional graphical models with either continuous or discrete variables. The package efficiently implements recent improvements in the Bayesian literature. The core of the BDgraph package consists of two main MCMC sampling algorithms efficiently implemented in C++ to maximize computational speed. In this paper, we give a brief overview of the methodology and illustrate the package's functionality in both toy examples and applications.