Abstract
In the following we give a systematic report on mean squared error matrix comparisons of competing biased estimators. Our approach is quite general: The parameter vector to be estimated is assumed to belong to a subset of the p-dimensional Euclidean space. However, to illustrate our results, we shall pay attention to the linear regression model where biased estimation is very popular. Especially we are interested in generalized ridge and restricted least squares estimation.
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Support by the Deutsche Forschungsgemeinschaft (DFG, grant number TR 253/1-1 (s*) and grant number STA 284/1-1 (s**)) is gratefully acknowledged.
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Trenkler, G., Toutenburg, H. Mean squared error matrix comparisons between biased estimators — An overview of recent results. Statistical Papers 31, 165–179 (1990). https://doi.org/10.1007/BF02924687
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DOI: https://doi.org/10.1007/BF02924687