  We compare three methods to measure the count-in-cell probability density
function of galaxies in a spectroscopic redshift survey. From this comparison
we found that when the sampling is low (the average number of object per cell
is around unity) it is necessary to use a parametric method to model the galaxy
distribution. We used a set of mock catalogues of VIPERS, in order to verify if
we were able to reconstruct the cell-count probability distribution once the
observational strategy is applied. We find that in the simulated catalogues,
the probability distribution of galaxies is better represented by a Gamma
expansion than a Skewed Log-Normal. Finally, we correct the cell-count
probability distribution function from the angular selection effect of the
VIMOS instrument and study the redshift and absolute magnitude dependency of
the underlying galaxy density function in VIPERS from redshift $0.5$ to $1.1$.
We found very weak evolution of the probability density distribution function
and that it is well approximated, independently from the chosen tracers, by a
Gamma distribution.
