Estimating and testing a structured covariance matrix for three-level multivariate data.(English)Zbl 1216.62095

Summary: This article considers an approach to estimating and testing a new Kronecker product covariance structure for three-level (multiple time points $$(p)$$, multiple sites $$(u)$$, and multiple response variables $$(q))$$ multivariate data. Testing of such covariance structure is potentially important for high dimensional multi-level multivariate data. The hypothesis testing procedure developed in this article can not only test the hypothesis for three-level multivariate data, but also can test many different hypotheses, such as blocked compound symmetry, for two-level multivariate data as special cases. The tests are implemented with two real data sets.

MSC:

 62H15 Hypothesis testing in multivariate analysis 62H12 Estimation in multivariate analysis 15A99 Basic linear algebra 65C60 Computational problems in statistics (MSC2010)
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References:

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