**A. Bobbio, A. Horváth, M. Telek**

This paper introduces a unified approach to phase-type
approximation in which the discrete and the continuous
phase-type models form a common model set. The models of
this common set are assigned with a non-negative real
parameter, the *scale factor*. The case when the scale
factor is strictly positive results in Discrete phase-type
distributions and the scale factor represents the time
elapsed in one step. If the scale factor is 0, the resulting
class is the class of Continuous phase-type
distributions. Applying the above view, it is shown that
there is no qualitative difference between the discrete and
the continuous phase-type models.

Based on this unified view of phase-type models one can choose the best phase-type approximation of a stochastic model by optimizing the scale factor.