| Abstract: | In this article, we consider the problem of testing a general multivariate linear hypothesis in a multivariate linear model when the N × p observation matrix is normally distributed with unknown covariance matrix, and N ≤ p. This includes the case of testing the equality of several mean vectors. A test is proposed which is a generalized version of the two-sample test proposed by Srivastava and Du (2008
Srivastava , M. S. ,
Du , M. ( 2008 ). A test for the mean vector with fewer observations than the dimension . J. Multivariate Anal. 99 : 386 – 402 .Crossref], Web of Science ®] , Google Scholar]). The asymptotic null and nonnull distributions are obtained. The performance of this test is compared, theoretically as well as numerically, with the corresponding generalized version of the two-sample Dempster (1958
Dempster , A. P. (1958). A high dimensional two sample significance test. Ann. Math. Statist. 29:995–1010.Crossref] , Google Scholar]) test, or more appropriately Bai and Saranadasa (1996
Bai , Z. ,
Saranadasa , H. ( 1996 ). Effect of high dimension: an example of a two sample problem . Statistica Sinica 6 : 311 – 329 .Web of Science ®] , Google Scholar]) test who gave its asymptotic version. |
