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Multiple comparisons of mean vectors with large dimension under general conditions
Authors:M. Rauf Ahmad
Affiliation:1. Department of Statistics, Uppsala University, Uppsala, Swedenrauf.ahmad@statistik.uu.se
Abstract:
ABSTRACT

Multiple comparisons for two or more mean vectors are considered when the dimension of the vectors may exceed the sample size, the design may be unbalanced, populations need not be normal, and the true covariance matrices may be unequal. Pairwise comparisons, including comparisons with a control, and their linear combinations are considered. Under fairly general conditions, the asymptotic multivariate distribution of the vector of test statistics is derived whose quantiles can be used in multiple testing. Simulations are used to show the accuracy of the tests. Real data applications are also demonstrated.
Keywords:Simultaneous inference  high-dimensional testing  pairwise comparisons
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