We point out that inliers adversely affect performance of the spatial
median and its generalization due to Gentleman. They are most deleteri
ous in the case of the median itself, and in the important setting of
two dimensions. There, the second term in a stochastic expansion of th
e median has a component with a Cauchy limiting distribution, and does
not have any finite moments. This term is substantially determined by
a small number of extreme, inlying data values. The implications for
bootstrap methods are significant, since the bootstrap is notoriously
poor in capturing properties of extremes. Indeed, the bootstrap does n
ot accurately approximate second-order features of the distribution of
the two-dimensional spatial median. We suggest a Winsorizing device f
or alleviating the effects of inliers. The issue of outliers is also d
iscussed. (C) 1997 Academic Press.