论文标题
矩阵变化$ t $分布的本地正常近似和概率度量界及其在Hotelling的$ t $统计中的应用
Local normal approximations and probability metric bounds for the matrix-variate $T$ distribution and its application to Hotelling's $T$ statistic
论文作者
论文摘要
在本文中，我们开发了局部扩展，以相同的协方差的中心矩阵变化$ t $密度与中心基质变异的正常密度的比率。这些近似值用于在相应诱导的度量之间在几个概率指标（例如总变化和Hellinger距离）上得出上限。这项工作将Shafiei＆Saberali（2015）和Ouimet（2022）的一些结果扩展到了矩阵变量设置。
In this paper, we develop local expansions for the ratio of the centered matrix-variate $T$ density to the centered matrix-variate normal density with the same covariances. The approximations are used to derive upper bounds on several probability metrics (such as the total variation and Hellinger distance) between the corresponding induced measures. This work extends some of the results of Shafiei & Saberali (2015) and Ouimet (2022) for the univariate Student distribution to the matrix-variate setting.
