论文标题
与均匀图相关的图形高斯模型与置换对称性
Graphical Gaussian models associated to a homogeneous graph with permutation symmetries
论文作者
论文摘要
我们考虑了随机向量$（z^1，\ ldots，z^p）$的多元中心高斯模型，其条件结构由均匀的图描述，并且在排列子组的作用下是不变的。以下论文涉及彩色图形高斯模型中的模型选择，当已知基础条件依赖图时。我们得出了精确参数的diConis-基督相结合的标准化常数的分析表达，并通过排列子组的作用在图形高斯模型类别中执行贝叶斯模型选择。我们用一个尺寸$ 5 $的玩具示例来说明结果。
We consider multivariate centered Gaussian models for the random vector $(Z^1,\ldots, Z^p)$, whose conditional structure is described by a homogeneous graph and which is invariant under the action of a permutation subgroup. The following paper concerns with model selection within colored graphical Gaussian models, when the underlying conditional dependency graph is known. We derive an analytic expression of the normalizing constant of the Diaconis-Ylvisaker conjugate prior for the precision parameter and perform Bayesian model selection in the class of graphical Gaussian models invariant by the action of a permutation subgroup. We illustrate our results with a toy example of dimension $5$.
