Minimum variance unbiased invariant estimation of variance components under normality |
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Authors: | S S Wulff |
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Institution: | Department of Statistics , University of Wyoming , Laramie, WY, 82071, USA |
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Abstract: | In a variance components model for normally distributed data, for a specified vector of linear combinations of the variance components, necessary and sufficient conditions are given under which the vector has a uniformly minimum variance unbiased translation-invariant estimator. The competing class of estimators is not restricted to those that are quadratic. For classification models, the conditions are translated into easy-to-check partial balance requirements on the incidence array. |
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Keywords: | Best unbiased estimator MINQUE Cramer-Rao lower bound Quadratic subspace Mixed-effects linear model Classification model ANOVA model |
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