Local normal approximations and probability metric bounds for the
matrix-variate distribution and its application to Hotelling's
statistic
Abstract
In this paper, we develop local expansions for the ratio of the centered matrix-variate 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.
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