  In 1956, Charles Stein published an article that was to forever change the
statistical approach to high-dimensional estimation. His stunning discovery
that the usual estimator of the normal mean vector could be dominated in
dimensions 3 and higher amazed many at the time, and became the catalyst for a
vast and rich literature of substantial importance to statistical theory and
practice. As a tribute to Charles Stein, this special issue on minimax
shrinkage estimation is devoted to developments that ultimately arose from
Stein's investigations into improving on the UMVUE of a multivariate normal
mean vector. Of course, much of the early literature on the subject was due to
Stein himself, including a key technical lemma commonly referred to as Stein's
Lemma, which leads to an unbiased estimator of the risk of an almost arbitrary
estimator of the mean vector.
