Facultad de Ciencias, Instituto de Estudios Superiores de Administración IESA, Universidad Central de Venezuela, Caracas 1010, DF, Venezuela
Copyright © 2009 Henryk Gzyl and Enrique Ter Horst. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
We present a new method, based on the method of maximum entropy in the
mean, which builds upon the standard method of maximum entropy, to improve the parametric estimation of a decay rate when the measurements are corrupted by large level of
noise and, more importantly, when the number of measurements is small. The method is
developed in the context on a concrete example: that of estimation of the parameter in an
exponential distribution. We show how to obtain an estimator with the noise filtered out,
and using simulated data, we compare the performance of our method with the Bayesian
and maximum likelihood approaches.