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: | , |
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| Format: | Article |
| Language: | English |
| Published: |
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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| Summary: | 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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| ISSN: | 1687-952X 1687-9538 |