Recently the termed \emph{multimatrix variate distributions} were proposed in \citet{dgcl:24a} as an alternative for univariate and vector variate copulas. The distributions are based on sample probabilistic dependent elliptically countered models and most of them are also invariant under this family of laws. Despite a large of results on matrix variate distributions since the last 70 years, the spherical multimatrix distributions and the associated probabilities on hyper cones can be computable. The multiple probabilities are set in terms of recurrent integrations allowing several matrix computation a feasible task. An application of the emerging probabilities is placed into a dynamic molecular docking in the SARS-CoV-2 main protease. Finally, integration over multimatrix Wishart distribution provides a simplification of a complex kernel integral in elliptical models under real normed division algebras and the solution was applied in elliptical affine shape theory.

翻译：最近，\citet{dgcl:24a}中提出的所谓“多矩阵变量分布”为单变量与向量变量copula提供了一种替代方案。这些分布基于样本概率相依的椭圆轮廓模型，且其中大多数在该族定律下也具有不变性。尽管过去70年间关于矩阵变量分布的研究成果颇丰，但球形多矩阵分布及其在超锥面上的相关概率仍可计算。多重概率通过递归积分形式设定，使得若干矩阵计算成为可行任务。本文将该新兴概率应用于SARS-CoV-2主要蛋白酶中的动态分子对接。最后，通过对多矩阵Wishart分布进行积分，简化了实赋范可除代数下椭圆模型中的复杂核积分，并将该解应用于椭圆仿射形状理论。