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Optimal elimination of nuisance parameters in mixed linear models. (English) Zbl 0760.62067
Author’s abstract: The vector parameter of the mean value of an observation vector in a mixed linear model (MLM) is supposed to be divided into necessary and nuisance vector parameters. A class of linear transformations of the observation vector eliminating the nuisance vector parameter which do not cause a loss of information about the necessary parameter is considered. The problem which of these transformations has the property that the same locally best quadratic estimator of variance components from the original and the transformed MLM is obtained is solved. Several kinds of estimators are investigated.

62J10 Analysis of variance and covariance (ANOVA)
62J05 Linear regression; mixed models
62F10 Point estimation
Full Text: EuDML
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