Powers of Some One-Sided Multivariate Tests with the Population Covariance Matrix Known up to ......
Powers of Some One-Sided Multivariate Tests with the Population Covariance Matrix Known up to a Multiplicative Constant
by Assoc. Prof. Samruam Chongcharoen School of Applied Statistics, National Institute of Development Administration Bangkapi, Bangkok 10240, Thailand Bahadur Singh 2401 W. Broadway, Columbia, MO 65203, USA F.T. Wright Department of Statistics, University of Missouri-Columbia, 222 Math Sciences Building, 810 Rollins Street, Columbia, MO 65211-4100, USA
For a multivariate normal population, Kudo (Biometrika 50 (1963) 403) and Shorack (Ann. Math. Statist. 38 (1967) 1740) derived the likelihood ratio tests of the null hypothesis that the mean vector is zero with a one-sided alternative for a known covariance matrix and for a covariance matrix which is known up to a multiplicative constant, respectively. Because these tests may be tedious to use, Tang et al. (Biometrika 76 (1989) 577) developed an approximate likelihood ratio test and Follmann (J. Amer. Statist. Assoc. 91 (1996) 854) proposed a one-sided modification of the usual chi-squared test for an unordered alternative. We consider a modification of Follmanns test which performs better than Follmanns test at some alternatives, and we derive expressions for the powers of the new test and Follmanns test for the cases considered here. For multivariate normal distributions with dimension no more than three and known covariance matrix, we consider the power functions of Kudos test and the TangGneccoGeller test. Using these exact results and Monte-Carlo simulations, we study the powers of these one-sided tests. ฉ 2002 Elsevier Science B.V. All rights reserved.
MSC: primary 62H15; secondary 62F03
Keywords: Follmanns test; Kudos test; Shoracks test; Simple order; Simple tree order; TangGneccoGeller test
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