Bayesian analysis of CCDM Models
  Creation of Cold Dark Matter (CCDM), in the context of Einstein Field
Equations, leads to negative creation pressure, which can be used to explain
the accelerated expansion of the Universe. In this work we tested six different
spatially flat models for matter creation using statistical tools, at light of
SN Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion
(BIC) and Bayesian Evidence (BE). These approaches allow to compare models
considering goodness of fit and number of free parameters, penalizing excess of
complexity. We find that JO model is slightly favoured over LJO/$\Lambda$CDM
model, however, neither of these, nor $\Gamma=3\alpha H_0$ model can be
discarded from the current analysis. Three other scenarios are discarded either
from poor fitting, either from excess of free parameters.
