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TESTS WITH OPTIMAL AVERAGE POWER IN MULTIVARIATE ANALYSIS
Samuel S. Wu, Hongying Li and George Casella
Vol. 16, No. 1 (January 2006), pp. 255-266
Published by: Institute of Statistical Science, Academia Sinica
Stable URL: http://www.jstor.org/stable/24307491
Page Count: 12
You can always find the topics here!Topics: Covariance, Statism, Weighting functions, Statistics, Matrices, Correlation coefficients, Power functions, Gaussian distributions, Sine function, Arithmetic mean
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It is well known that in a general multi-parameter setting, there may not exist any unique best test. More importantly, unlike the univariate case, the power of different test procedures could vary remarkably. In this article we extend results of Hsu (1945) and introduce a new class of tests that have best average power for multivariate linear hypotheses. A simple method to implement the new tests is also provided.
Statistica Sinica © 2006 Institute of Statistical Science, Academia Sinica