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.