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Minimax adjustment technique in a parameter restricted linear model. (English) Zbl 0844.62059

Summary: We consider an approach yielding a minimax estimator in the linear regression model with a priori information on the parameter vector, e.g., ellipsoidal restrictions. This estimator is computed directly from the loss function and can be motivated by the general Pitman nearness criterion. It turns out that this approach coincides with the projection estimator which is obtained by projecting an initial arbitrary estimate on the subset defined by the restrictions.

MSC:

62J05 Linear regression; mixed models
62C20 Minimax procedures in statistical decision theory
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