For a p-dimensional normal distribution with mean vector [theta] and covariance matrix Ip, it is known that the maximum likelihood estimator [theta] of [theta] with p[greater-or-equal, slanted]3 is inadmissible under the squared loss. The present paper considers possible extensions of the result...

This paper considers the linear regression model with multiple stochastic regressors, intercept, and errors that have undefined means. This model is of interest from a robustness perspective as a polar case. Generally, least squares estimators are inconsistent in this context. It is shown,...