  This study shows how road traffic networks events, in particular road
accidents on blackspots, can be modelled with simple probabilistic
distributions. We considered the number of accidents and the number of deaths
on Spanish blackspots in the period 2003-2007, from Spanish General Directorate
of Traffic (DGT). We modelled those datasets, respectively, with the discrete
generalized Pareto distribution (a discrete parametric model with three
parameters) and with the discrete Lomax distribution (a discrete parametric
model with two parameters, and particular case of the previous model). For
that, we analyzed the basic properties of both parametric models: cumulative
distribution, survival, probability mass, quantile and hazard functions,
genesis and rth-order moments; applied two estimation methods of their
parameters: the $\mu$ and ($\mu+1$) frequency method and the maximum likelihood
method; and used two goodness-of-fit tests: Chi-square test and discrete
Kolmogorov-Smirnov test based on bootstrap resampling. We found that those
probabilistic models can be useful to describe the road accident blackspots
datasets analyzed.
