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

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 r...

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Vydáno v:Statistical papers (Berlin, Germany) Ročník 62; číslo 5; s. 2109 - 2118
Hlavní autoři: Zmyślony, Roman, Kozioł, Arkadiusz
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2021
Springer Nature B.V
Témata:
Covariance matrix
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Finance
Hypotheses
Insurance
Management
Mathematical analysis
Mathematics and Statistics
Mean
Multivariate analysis
Normality
Operations Research/Decision Theory
Probability Theory and Stochastic Processes
Research Article
Statistical tests
Statistics
Statistics for Business
Structure of mean vector
Structure of covariance matrices
Positive and negative part of estimator
Best unbiased estimator
Block compound symmetric covariance structure
Double multivariate data
Testing hypotheses
ISSN:0932-5026, 1613-9798
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Shrnutí: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).
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ISSN:0932-5026
1613-9798
DOI:10.1007/s00362-020-01182-4