The Superiorities of Minimum Bayes Risk Linear Unbiased Estimator in Two Seemingly Unrelated Regressions

摘要

In the system of two seemingly unrelated regressions, the minimum Bayes risk linear unbiased (MBRLU) estimators of regression parameters are derived. The superiorities of the MBRLU estimators over the classical estimators are investigated, respectively, in terms of the mean square error matrix (MSEM) criterion, the predictive Pitman closeness (PRPC) criterion and the posterior Pitman closeness (PPC) criterion.