Abstract
The general linear hypothesis is usually tested by means of anF-statistic dependent on the least squares estimator. In this paper, a class of linear estimators is identified which can also serve as a basis for such anF-statistic. Conditions are derived under which thisF-statistic coincides with the usual one. This opens the possibility of constructing minimax-estimators which dominate LS with respect to risk, yielding the same test results.
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Support by Deutsche Forschungsgemeinschaft, Grant No. Tr 253/1-2 is gratefully acknowledged.
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Stahlecker, P., Knautz, H. & Trenkler, G. Hypothesis testing using affine linear estimators. Acta Appl Math 43, 153–158 (1996). https://doi.org/10.1007/BF00046996
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DOI: https://doi.org/10.1007/BF00046996