In univariate calibration, two standard estimators are usually opposed: the classical estimator and the inverse regression estimator. Controversies have followed the use of both estimators and we consider them from a decision-theoretic perspective, establishing the inadmissibility of the...

The usual confidence set for a multivariate mean vector can be improved upon by recentering the set at a Stein-type estimator: this fact is known to be true under many different distributional assumptions. Thus far, however, the case of unknown variance has not been dealt with analytically. In...

The estimation of the location parameter of a spherically symmetric distribution was greatly improved by Berger and Brandwein. But the authors conditions on the shrinkage estimators depend upon the complete knowledge, up to the location parameter, of the distribution of the observations. We give...