  In the estimation of the mean matrix in a multivariate normal distribution,
the generalized Bayes estimators with closed forms are provided, and the
sufficient conditions for their minimaxity are derived relative to both matrix
and scalar quadratic loss functions. The generalized Bayes estimators of the
covariance matrix are also given with closed forms, and the dominance
properties are discussed for the Stein loss function.
