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• W2255024256 abstract "The problem of testing the population mean vector of high-dimensional multivariate data is considered. Inspired by Roy’s union–intersection test, a generalized high-dimensional likelihood ratio test for the normal population mean vector is proposed. The p-value for the test is obtained by using randomization method, which does not rely on assumptions about the structure of the covariance matrix. An interpretation of the new statistic is given, which does not rely on the normality assumption. Hence the proposed test is also available for non-normal multivariate population. Simulation studies show that the new test offers higher power than other two competing tests when the variables are dependent and performs particularly well for non-normal multivariate population." @default.
• W2255024256 created "2016-06-24" @default.
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• W2255024256 date "2016-07-01" @default.
• W2255024256 modified "2023-10-03" @default.
• W2255024256 title "A generalized likelihood ratio test for normal mean when <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML altimg=si27.gif display=inline overflow=scroll><mml:mi>p</mml:mi></mml:math> is greater than <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML altimg=si28.gif display=inline overflow=scroll><mml:mi>n</mml:mi></mml:math>" @default.
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• W2255024256 doi "https://doi.org/10.1016/j.csda.2016.01.006" @default.
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