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We consider the problem of inferring the conditional independence graph (CIG) of a stationary multivariate Gaussian time series. A p-variate Gaussian time series graphical model associated with an undirected graph with p vertices is defined as the family of time series that obey the conditional independence restrictions implied by the edge set of the graph. In some existing methods, partial cohere...

Edge Exclusion Tests for Graphical Model Selection: Complex Gaussian Vectors and Time Series