On perfectness in Gaussian graphical models

3 Sep 2019Arash A. AminiBryon AragamQing Zhou

Knowing when a graphical model is perfect to a distribution is essential in order to relate separation in the graph to conditional independence in the distribution, and this is particularly important when performing inference from data. When the model is perfect, there is a one-to-one correspondence between conditional independence statements in the distribution and separation statements in the graph... (read more)

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