  Projection Pursuit methodology permits to solve the difficult problem of
finding an estimate of a density defined on a set of very large dimension. In
his seminal article, Huber (see "Projection pursuit", Annals of Statistics,
1985) evidences the interest of the Projection Pursuit method thanks to the
factorisation of a density into a Gaussian component and some residual density
in a context of Kullback-Leibler divergence maximisation. In the present
article, we introduce a new algorithm, and in particular a test for the
factorisation of a density estimated from an iid sample.
