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Journal of Probability and Statistics
Volume 2009, Article ID 563281, 13 pages
Research Article

Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean

Facultad de Ciencias, Instituto de Estudios Superiores de Administración IESA, Universidad Central de Venezuela, Caracas 1010, DF, Venezuela

Received 5 December 2008; Revised 26 February 2009; Accepted 30 March 2009

Academic Editor: Nikolaos Limnios

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.