Abstract
In this note a decision rule presented by Suich and Derringer [12] for aiding model validation is examined and contrasted to others in the literature. These decision rules which lead to preliminary test estimators are compared under squared error loss to the risk of the conventional estimator. Finally an estimator is identified which is uniformly superior to (dominates) the pretest estimator over the entire range of the parameter space.
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