= Gaussian graphical model
{c}
{title2=$\Omega=\Sigma^{-1},\quad\Omega_{jk}=0\iff\{j,k\}\notin E$}
For a nondegenerate <multivariate normal distribution>, the <conditional independence graph> is read from zeros in its <precision matrix>. Conditional independence of two components given all others is equivalent to a zero cross term in their conditional Gaussian quadratic density, hence to $\Omega_{jk}=0$. It does not generally correspond to a zero in the <covariance matrix>.
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