  We explore the properties of discrete-time stochastic processes with a
bounded state space, whose deterministic limit is given by a map of the unit
interval. We find that, in the mesoscopic description of the system, the large
jumps between successive iterates of the process can result in probability
leaking out of the unit interval, despite the fact that the noise is
multiplicative and vanishes at the boundaries. By including higher-order terms
in the mesoscopic expansion, we are able to capture the non-Gaussian nature of
the noise distribution near the boundaries, but this does not preclude the
possibility of a trajectory leaving the interval. We propose a number of
prescriptions for treating these escape events, and we compare the results with
those obtained for the metastable behavior of the microscopic model, where
escape events are not possible. We find that, rather than truncating the noise
distribution, censoring this distribution to prevent escape events leads to
results which are more consistent with the microscopic model. The addition of
higher moments to the noise distribution does not increase the accuracy of the
final results, and it can be replaced by the simpler Gaussian noise.
