摘要：We propose improvements under squared error loss of the minimum risk equivari-
ant and the linear minimax estimators for estimating the location parameter of a
p-variate spherically symmetric distribution, with restricted to a ball of radius m
centered at the origin. Our construction of explicit improvements relies on a multi-
variate version of Kubokawa’s Integral Expression of Risk Difference (IERD) method.
Applications are given for univariate distributions, for the multivariate normal, and
for scale mixture of multivariate normal distributions.
关键词：decision theory; spherical symmetric distribution; restricted parameter; minimum
risk equivariant estimator; linear minimax estimator; dominating estimators; squared
error loss
