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

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 measuremen...

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Main Authors: Henryk Gzyl, Enrique Ter Horst
Format: Article
Language:English
Published: Wiley 2009-01-01
Series:Journal of Probability and Statistics
Online Access:http://dx.doi.org/10.1155/2009/563281
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author Henryk Gzyl
Enrique Ter Horst
author_facet Henryk Gzyl
Enrique Ter Horst
author_sort Henryk Gzyl
collection DOAJ
description 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.
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institution Kabale University
issn 1687-952X
1687-9538
language English
publishDate 2009-01-01
publisher Wiley
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series Journal of Probability and Statistics
spelling doaj-art-672e904148cd4d88b3f1ca76057abf742025-02-03T05:47:07ZengWileyJournal of Probability and Statistics1687-952X1687-95382009-01-01200910.1155/2009/563281563281Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the MeanHenryk Gzyl0Enrique Ter Horst1Facultad de Ciencias, Instituto de Estudios Superiores de Administración IESA, Universidad Central de Venezuela, Caracas 1010, DF, VenezuelaFacultad de Ciencias, Instituto de Estudios Superiores de Administración IESA, Universidad Central de Venezuela, Caracas 1010, DF, VenezuelaWe 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.http://dx.doi.org/10.1155/2009/563281
spellingShingle Henryk Gzyl
Enrique Ter Horst
Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean
Journal of Probability and Statistics
title Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean
title_full Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean
title_fullStr Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean
title_full_unstemmed Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean
title_short Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean
title_sort recovering decay rates from noisy measurements with maximum entropy in the mean
url http://dx.doi.org/10.1155/2009/563281
work_keys_str_mv AT henrykgzyl recoveringdecayratesfromnoisymeasurementswithmaximumentropyinthemean
AT enriqueterhorst recoveringdecayratesfromnoisymeasurementswithmaximumentropyinthemean