Conditional independence graph
= Conditional independence graph
For a random vector indexed by vertices $V$, its conditional independence graph is the undirected graph with $u-v$ absent exactly when $Z_u\perp Z_v\mid Z_{V\setminus\{u,v\}}$. In a nonsingular <multivariate normal distribution>, its edges are the nonzero off-diagonal entries of the <precision matrix>.