We present a nonparametric method for galaxy clustering in
astronomical sky surveys. We show that the cosmological definition of
clusters of galaxies is equivalent to density
contour clusters (Hartigan, 1975)

where

is a
probability
density function. The plug-in estimator

is
used to estimate

where

is the multivariate kernel
density estimator. To choose the optimal smoothing parameter, we use
cross-validation and the plug-in method and show that cross-validation
method
outperforms the plug-in method in our case. A new cluster catalogue
based on the plug-in estimator is compared to existing cluster
catalogs, the Abell and EDCCI. Our result is more consistent with the
EDCCI than
with the Abell, which is the most widely used catalogue. We present a
practical
algorithm for local smoothing and use the smoothed bootstrap to asses the
validity of clustering results.