A note on the comparison of minimax linear and mixed regression estimation of regression coefficients when prior estimates are available

When prior estimates of regression coefficients along with their stan¡ dard errors or their variance covariance matrix are available, they can be incorporated into the estimation procedure through minimax linear and mixed regression approaches. It is demonstrated that the mixed regres¡ sion approach provides more efficient estimators, at least asymptotically, in comparison to the minimax linear approach with respect to the criterion of variance covariance matrix.