n graphical models (GGM). The methods are organized around two general approaches for Bayesian inference: (1) estimation and (2) hypothesis testing. The key distinction is that the former focuses on either the posterior or posterior predictive distribution [@Gelman1996a; see section 5 in @rubin1984bayesianly] , whereas the latter focuses on model comparison with the Bayes factor [@Jeffreys1961; @Kass1995].</p>
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<h2 id="what-is-a-gaussian-graphical-model-">What is a Gaussian Graph