  Several methods can be used to perform statistical inference of primary
composition of cosmic rays measured with water Cerenkov detectors as those in
use at the Pierre Auger Southern Observatory. In the present work we assess the
impact of additional information about the number of muons in the air shower,
on the problem of statistical primary mass discrimination. Several tools are
studied, including neural networks, principal component analysis and
traditional methods in current use in the field. For our case study we use
hypothetical plastic scintillators as muon counters, buried at the side and
outside the shade of the water Cerenkov tanks. The study is extended to protons
and Fe nuclei impinging on an array with two different spacings, 750 and 1500 m
and, therefore, suitable to the 1-10 EeV energy range. A prototype of such a
detector is under construction.
