  We investigate the performance of spherical wavelets in discriminating
between standard inflationary models (Gaussian) and non-Gaussian models. For
the later we consider small perturbations of the Gaussian model in which an
artificially specified skewness or kurtosis is introduced through the Edgeworth
expansion. By combining all the information present in all the wavelet scales
with the Fisher discriminant, we find that the spherical Mexican Hat wavelets
are clearly superior to the spherical Haar wavelets. The former can detect
levels of the skewness and kurtosis of ~1% for 33' resolution, an order of
magnitude smaller than the later. Also, as expected, both wavelets are better
for discriminating between the models than the direct consideration of moments
of the temperature maps. The introduction of instrumental white noise in the
maps, S/N=1, does not change the main results of this paper.
