We consider multivariate centered Gaussian models for the random variable $Z=(Z_1,\ldots, Z_p)$, invariant under the action of a subgroup of the group of permutations on $\{1,\ldots, p\}$. Using the representation theory of the symmetric group on the field of reals, we derive the distribution of the maximum likelihood estimate of the covariance parameter $\Sigma$ and also the analytic expression of the normalizing constant of the Diaconis-Ylvisaker conjugate prior for the precision parameter $K=\Sigma^{-1}$. We can thus perform Bayesian model selection in the class of complete Gaussian models invariant by the action of a subgroup of the symmetric group, which we could also call complete RCOP models. We illustrate our results with a toy example of dimension $4$ and several examples for selection within cyclic groups, including a high dimensional example with $p=100$.
翻译:我们考虑的是随机变量$( ⁇ 1,\ldots, ⁇ p) 的多变量核心高斯模型, 由一组变数分组在 $1,\ldots, p ⁇ 1 的动作下进行。 使用对称组在实数领域的表示理论, 我们得出共差参数最大可能性估计值$\Sigma$的分布, 以及 Diaconis- Ylvisaker conjugate 常数的解析表达, 之前的精确参数$K ⁇ Sigma_ _1美元。 因此, 我们可以通过一个对称组的分组的行动在完整的高斯变数模型类别中进行巴伊西亚模型选择, 我们也可以称之为完整的 RCOP 模型。 我们用一个维度的微小例子来说明我们的结果, 4美元, 和几个用于在周期组中选择的示例, 包括一个以 $p=100美元的高维示例 。