A colored Gaussian graphical model is a linear concentration model in which equalities among the concentrations are specified by a coloring of an underlying graph. The model is called RCOP if this coloring is given by the edge and vertex orbits of a subgroup of the automorphism group of the graph. We show that RCOP Gaussian graphical models on block graphs are toric in the space of covariance matrices and we describe Markov bases for them. To this end, we learn more about the combinatorial structure of these models and their connection with Jordan algebras.
翻译:Gaussian 颜色图形模型是一种线性浓度模型,其浓度的等值由底图的颜色显示。如果该模型由图形自动形态组分组的边缘和顶点轨道提供,则该模型称为 RCOP。我们显示块形图形上的 RCOP Gaussian 图形模型在共变量矩阵空间中是富集的,我们为其描述Markov 基础。为此,我们更多地了解这些模型的组合结构及其与Jordan代数的联系。