Two-sample Behrens-Fisher problems for high-dimensional data: a normal reference scale-invariant test.

ABSTRACT: For high-dimensional two-sample Behrens-Fisher problems, several non-scale-invariant and scale-invariant tests have been proposed. Most of them impose strong assumptions on the underlying group covariance matrices so that their test statistics are asymptotically normal. However, in practice, these assumptions may not be satisfied or hardly be checked so that these tests may not be able to maintain the nominal size well in practice. To overcome this difficulty, in this paper, a normal reference scale-invariant test is proposed and studied. It works well by neither imposing strong assumptions on the underlying group covariance matrices nor assuming their equality. It is shown that under some regularity conditions and the null hypothesis, the proposed test and a chi-square-type mixture have t

SUBMITTER: Zhang L 

PROVIDER: S-EPMC9930866 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature