The problem of assessing numerical values of possibility distributions is c
onsidered in the paper. Particularly, we are interested in estimating the p
ossibility values from a data set. The proposed estimation methods are base
d on the idea of transforming a probability distribution (obtained from the
data set) into a possibility one. They also take into account that smaller
data base size involve a greater uncertainty about the model and therefore
, less precise assessments should be obtained in such cases. Moreover, in o
rder to validate the estimated joint possibility distribution, a set of pro
perties which guarantee that we obtain reasonable results will be studied.
Finally, we are interested in analyzing the feasibility of the decisions or
the conclusions that can be obtained by manipulating the estimated possibi
lity distribution, so that some of the properties of this distribution, aft
er applying to it the marginalization and conditioning operators, are also
studied.