Abstract
This article examines the question of admissibility of the restricted least squares (RLS) estimator applied to the linear model , where . Straightforward proofs based on generalizations of the results of Cohen (1966) demonstrate that RLS estimators are admissible under predictive squared error risk iff the dimension of the β parameter space minus the number of linearly independent restrictions on β is less than three. A Stein-type estimator that dominates the inadmissible RLS estimator is presented. Some extensions of the results are indicated.
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