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- W2077599785 abstract "For a class of linear models with normally distributed error structures, necessary and sufficient conditions are given where the maximum likelihood (ML) and restricted maximum likelihood (REML) estimators of the parameters are functions of the ordinary least squares (OLS) and analysis of variance (ANOVA) estimators. These results are then used to extend the Gauss-Markov theorem to a broad class of error structures. The conditions are compared to equivalent results in the literature. Examples are presented to illustrate the problem." @default.
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- W2077599785 title "Maximum likelihood and restricted maximum likelihood estimators as functions of ordinary least squares and analysis of variance estimators" @default.
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- W2077599785 doi "https://doi.org/10.1080/03610929608831718" @default.
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