  We study the effect on the distribution of return periods of rare events of
the presence in a time series of finite-term correlations with non-exponential
decay. Precisely, we analyze the auto-correlation function and the statistics
of the return intervals of extreme values of the resistance fluctuations
displayed by a resistor with granular structure in a nonequilibrium stationary
state. The resistance fluctuations, $\delta R$, are calculated by Monte Carlo
simulations using the SBRN model introduced some years ago by Pennetta,
Tref\'an and Reggiani and based on a resistor network approach. A rare event
occurs when $\delta R$ overcomes a threshold value $q$ significantly higher
than the average value of the resistance. We have found that for highly
disordered networks, when the auto-correlation function displays a
non-exponential decay but yet the resistance fluctuations are characterized by
a finite correlation time, the distribution of return intervals of the extreme
values is well described by a stretched exponential, with exponent largely
independent of the threshold $q$. We discuss this result and some of the main
open questions related to it, also in connection with very recent findings by
other authors concerning the observation of stretched exponential distributions
of return intervals of extreme events in long-term correlated time series.
