|
|||||
 |
|
|
|
|
|
|
Computing maximum
likelihood estimates for Gaussian graphical models with
Macaulay2
Carlos Améndola, Luis David García Puente, Roser Homs, Olga Kuznetsova and Harshit J. Motwani
Vol. 12 (2022), 1–10
|
Abstract |
|
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. |
Keywords
algebraic statistics, Gaussian graphical models, loopless
mixed graphs, MLE
|
Mathematical Subject Classification
Primary: 62F10, 62H22, 62R01
|
Supplementary materialMacaulay2 package for computing the maximum likelihood estimates of Gaussian graphical models |
Milestones
Received: 22 December 2020
Revised: 30 November 2021
Accepted: 14 March 2022
Published: 20 November 2022
|
Authors |
| Carlos Améndola | |
| Max Planck Institute for Mathematics
in the Sciences Leipzig Germany |
|
| Luis David García Puente | |
| Department of Mathematics and
Computer Science Colorado College Colorado Springs, CO United States |
|
| Roser Homs | |
| Department of Mathematics Technical University of Munich Munich Germany |
|
| Olga Kuznetsova | |
| Department of Mathematics and
Systems Analysis Aalto University Aalto Finland |
|
| Harshit J. Motwani | |
| Department of Mathematics: Algebra
and Geometry Ghent University Ghent Belgium |
|
