  We present the function J as a morphological descriptor for point patterns
formed by the distribution of galaxies in the Universe. This function was
recently introduced in the field of spatial statistics, and is based on the
nearest neighbor distribution and the void probability function. The J
descriptor allows to distinguish clustered (i.e. correlated) from ``regular''
(i.e. anti-correlated) point distributions. We outline the theoretical
foundations of the method, perform tests with a Matern cluster process as an
idealised model of galaxy clustering, and apply the descriptor to galaxies and
loose groups in the Perseus-Pisces Survey. A comparison with mock-samples
extracted from a mixed dark matter simulation shows that the J descriptor can
be profitably used to constrain (in this case reject) viable models of cosmic
structure formation.
