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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Format: | Article |
Language: | English |
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Wiley
2009-01-01
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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. |
format | Article |
id | doaj-art-672e904148cd4d88b3f1ca76057abf74 |
institution | Kabale University |
issn | 1687-952X 1687-9538 |
language | English |
publishDate | 2009-01-01 |
publisher | Wiley |
record_format | Article |
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 |