Maximum Likelihood Estimation of Variance Components for a Multivariate Mixed Model with Equal Design Matrices

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Abstract
An algorithm is described for estimating variance and covariance components by restricted maximum likelihood for a multivariate mixed two-way classification with equal design matrices. The procedure involves a transformation to canonical scale, effectively reducing a q-variate analysis to q corresponding univariate analyses. A small numerical example is given as well as a large-scale practical application.

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