An analysis of a multivariate two-way model with interaction and no replication
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In this paper, we consider the problem of testing the hypothesis of no interaction in the multivariate two-way classification model with one observation per cell. If the error covariance matrix is unknown, we suggest pseudo-maximum likelihood estimation (PMLE) of the parameters and give the invariant test for the hypothesis of no interaction. Further, we develop also some tests for the case of an unknown diagonal positive definite error covariance matrix.
Key wordsAnalysis of variance interaction pseudo-maximum likelihood estimate maximal invariant invariant test
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