We consider the estimation of ∑ of the p-dimensional normal distribution N{sub}p(0, ∑) under the restriction where the eigenvalues of ∑ have an upper or lower bound. From a decision-theoretic point of view, we evaluate the performance of the REML (restricted maximum likelihood estimator) with Stein's loss function and propose another estimator that dominates the REML.
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