  In this paper, we address the problem of estimating a covariance matrix of a
multivariate Gaussian distribution, relative to a Stein loss function, from a
decision theoretic point of view. We investigate the case where the covariance
matrix is invertible and the case when it is non--invertible in a unified
approach.
