  Non-parametric estimation of a multivariate density estimation is tackled via
a method which combines traditional local smoothing with a form of global
smoothing but without imposing a rigid structure. Simulation work delivers
encouraging indications on the effectiveness of the method. An application to
density-based clustering illustrates a possible usage.

Methodology;Machine Learning