  The purpose of this note is to show how the method of maximum entropy in the
mean (MEM) may be used to improve parametric estimation when the measurements
are corrupted by large level of noise. The method is developed in the context
on a concrete example: that of estimation of the parameter in an exponential
distribution. We compare the performance of our method with the bayesian and
maximum likelihood approaches.
