LIMITING ADMISSIBLE ESTIMATORS FOR VARIANCE-COMPONENTS

Simultaneous estimation of the vector of the variance components for mixed and random models under the quadratic loss function is considered. For a large class of such models there are identified classes of admissible biased invariant quadratic estimators that are better than some admissible unbiased estimators. Numerous numerical results presented in the paper show that for many of the commonly used balanced models the improvements in the quadratic risk may be considerable over a large set of the parameter space. © 1990 Taylor & Francis Group, LLC. All rights reserved.