Presents computing methods for variance component estimation. These methods are designed to handle large sample survey or animal breeding experiments in which the random effects may have thousands of levels. The underlying theoretical technique, MIVQUEO (with V=1), has been shown to yield unbiased, locally best, admissible, and asymptotically consistent estimators.
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