Computing maximum likelihood estimates for Gaussian graphical models with Macaulay2
Carlos Améndola, Luis David García Puente, Roser Homs, Olga Kuznetsova, Harshit J. Motwani · Journal of Software for Algebra and Geometry · 2022
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.2020 Mathematics Subject Classification.62R01, 14-04, 62H22.Key words and phrases.algebraic statistics, Gaussian graphical models, loopless mixed graphs, maximum likelihood estimates.1 GraphicalModelsMLE version 0.3 is included in Macaulay2 version 1.17, the revised Graphi-calModelsMLE version 1.0 is available at https://github.com/roserhp/GraphicalModelsMLEand is expected to appear in Macaulay2 version 1.20.