论文标题
使用MacAulay的高斯图形模型计算最大似然估计2
Computing Maximum Likelihood Estimates for Gaussian Graphical Models with Macaulay2
论文作者
论文摘要
我们介绍了用于计算计算机代数系统Macaulay2中高斯图形模型的最大似然估计（MLE）的“ GraphicalModelSmle”。该软件包允许计算MLE的无环混合图类别。其他功能使用户可以探索模型的基本代数结构，例如其最大似然度和分数方程的理想。
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.
