Abstract
For a seemingly unrelated regression system with the assumption of normality, a necessary and sufficient condition for the existence of the Uniformly Minimum Risk Unbiased (UMRU) estimator of regression coefficients under strictly convex loss is obtained; it is proved that any unbiased estimator can not improve the least squares estimator; it is also shown that no UMRU estimator exists under missing observations.
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