  In multiple criteria decision aiding, very often the alternatives are
compared by means of a value function compatible with the preferences expressed
by the Decision Maker. The problem is that, in general, there is a plurality of
compatible value functions, and providing a final recommendation on the problem
at hand considering only one of them could be considered arbitrary to some
extent. For such a reason, Stochastic Multicriteria Acceptability Analysis
gives information in statistical terms by taking into account a sample of
models compatible with the provided preferences. These statistics are given
assuming the existence of a probability distribution in the space of value
functions being defined a priori. In this paper, we propose some methods aiming
to build a probability distribution on the space of value functions considering
the preference information given by the Decision Maker. To prove the goodness
of our proposal we performed an extensive set of simulations. Moreover, a
sensitivity analysis on the variables of our procedure has been done as well.
