Ratio F test for testing simultaneous hypotheses in models with blocked compound symmetric covariance structure

Roman Zmyślony () and Arkadiusz Kozioł ()
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Roman Zmyślony: University of Zielona Góra
Arkadiusz Kozioł: University of Zielona Góra

Statistical Papers, 2021, vol. 62, issue 5, No 3, 2109-2118

Abstract: Abstract This article deals with testing simultaneous hypotheses about the mean structure and the covariance structure in models with blocked compound symmetric (BCS) covariance structure. Considered models are used for double multivariate data, which means that m-variate vector of observation is measured repeatedly over u levels of some factor on each of n individual. Additionally, the assumption of multivariate normality for this type of data is made. We use framework of ratio of positive and negative parts of best unbiased estimators to obtain simultaneous F test. The test statistic is constructed as a ratio of test statistics for testing single hypotheses about the mean vector and the covariance matrix. In simulation study power of obtained test is compared with powers of three other F tests—two for testing single hypotheses and one for testing simultaneous hypotheses, whose test statistic is convex combination of test statistics of these two single F tests. The problem of simultaneous testing of the mean vector and covariance matrix was also consider in paper (Hyodo and Nishiyama, Commun Stat Theory Methods, https://doi.org/10.1080/03610926.2019.1639751 , 2019).

Keywords: Best unbiased estimator; Block compound symmetric covariance structure; Double multivariate data; Positive and negative part of estimator; Structure of covariance matrices; Structure of mean vector; Testing hypotheses (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s00362-020-01182-4

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