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Computing Maximum Likelihood Estimates for Gaussian Graphical Models with Macaulay2

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arxiv 2012.11572 v3 pith:6F2N2IVH submitted 2020-12-21 stat.CO math.AC

Computing Maximum Likelihood Estimates for Gaussian Graphical Models with Macaulay2

Carlos Am\'endola , Luis David Garc\'ia Puente , Roser Homs , Olga Kuznetsova , Harshit J. Motwani This is my paper
classification stat.CO math.AC
keywords likelihoodmaximumallowscomputingestimatesgaussiangraphicalmacaulay2
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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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