BGGM: Bayesian Gaussian Graphical Models in R

Abstract

The R package BGGM provides tools for making Bayesian inference in Gaussian graphical models (GGM). The methods are organized around two general approaches for Bayesian in- ference: (1) estimation and (2) hypothesis testing. The key distinction is that the former focuses on either the posterior or posterior predictive distribution (Gelman, Meng, & Stern, 1996; see section 5 in Rubin, 1984) , whereas the latter focuses on model comparison with the Bayes factor (Jeffreys, 1961; Kass & Raftery, 1995)