Finite-sample bounds for the multivariate Behrens-Fisher distribution with proportional covariances

Abstract: The Behrens-Fisher problem is a well-known hypothesis testing problem in statistics concerning two-sample mean comparison. In this article, we confirm one conjecture in Eaton and Olshen (1972), which provides stochastic bounds for the multivariate Behrens-Fisher test statistic under the null hypothesis. We also extend their results on the stochastic ordering of random quotients to the arbitrary finite dimensional case. This work can also be seen as a generalization of Hsu (1938) that provided the bounds for the univariate Behrens-Fisher problem. The results obtained in this article can be used to derive a testing procedure for the multivariate Behrens-Fisher problem that strongly controls the Type I error.