Admissible Bayes equivariant estimation of location vectors for spherically symmetric distributions with unknown scale

Abstract: This paper investigates estimation of the mean vector under invariant quadratic loss for a spherically symmetric location family with a residual vector with density of the form $ f(x,u)=\eta^{(p+n)/2}f(\eta{|x-\theta|^2+|u|^2}) $, where $\eta$ is unknown. We show that the natural estimator $x$ is admissible for $p=1,2$. Also, for $p\geq 3$, we find classes of generalized Bayes estimators that are admissible within the class of equivariant estimators of the form ${1-\xi(x/|u|)}x$. In the Gaussian case, a variant of the James--Stein estimator, $[1-{(p-2)/(n+2)}/{|x|^2/|u|^2+(p-2)/(n+2)+1}]x$, which dominates the natural estimator $x$, is also admissible within this class. We also study the related regression model.