  Priebe et al. (2001) introduced the class cover catch digraphs and computed
the distribution of the domination number of such digraphs for one dimensional
data. In higher dimensions these calculations are extremely difficult due to
the geometry of the proximity regions; and only upper-bounds are available. In
this article, we introduce a new type of data-random proximity map and the
associated (di)graph in $\mathbb R^d$. We find the asymptotic distribution of
the domination number and use it for testing spatial point patterns of
segregation and association.
