Shrinkage estimation of the regression parameters with multivariate normal errors

In the linear model y = Xf3 + e with the errors distributed as normal, we obtain generalized least square (GLS) , restricted GLS (RGLS), prelim- inary test (PT), Stein-type shrinkage (S) and positive-rule shrinkage (PRS) estimators for regression vector parameter /? when the covariance structure in known. We compare the quadratic risks of the underlying estimators and propose the dominance orders of the five estimators.