  In spatial statistics, point processes are often assumed to be isotropic
meaning that their distribution is invariant under rotations. Statistical tests
for the null hypothesis of isotropy found in the literature are based either on
asymptotics or on Monte Carlo simulation of a parametric null model. Here, we
present a nonparametric test based on resampling the Fry points of the observed
point pattern. Empirical levels and powers of the test are investigated in a
simulation study for four point process models with anisotropy induced by
different mechanisms. Finally, a real data set is tested for isotropy.
