Papers › Computing Maximum Likelihood Estimates for Gaussian Graphical Models with Macaulay2
Computing Maximum Likelihood Estimates for Gaussian Graphical Models with Macaulay2
Carlos Améndola, Luis David García Puente, Roser Homs, Olga Kuznetsova, Harshit J. Motwani
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We introduce the package "GraphicalModelsMLE" for computing the maximum likelihood estimates (MLEs) of a Gaussian graphical model in the computer algebra system Macaulay2. This package allows the computation of MLEs for the class of loopless mixed graphs. Additional functionality allows the user to explore the underlying algebraic structure of the model, such as its maximum likelihood degree and the ideal of score equations.
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