  Time series are characterized by complex memory and/or distribution patterns.
In this letter we show that models obeying to different statistics may equally
reproduce some pattern of a time series. In particular we discuss the
difference between L\'evy-walk and fractal Gaussian intermittent signals and
show that the adoption of complementary scaling analysis techniques may be
useful to distinguish the two cases. Finally, we apply this methodology to the
earthquake occurrences in California and suggest the possibility that
earthquake occurrences are described by a \textit{colored} (= `long-range
correlated') Generalized Poisson model.
