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Finite-Sample Bounds on the Accuracy of Plug-In Estimators of Fisher Information

Author(s): Cao, Wei; Dytso, Alex; Fauss, Michael; Poor, H. Vincent

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dc.contributor.authorCao, Wei-
dc.contributor.authorDytso, Alex-
dc.contributor.authorFauss, Michael-
dc.contributor.authorPoor, H. Vincent-
dc.identifier.citationCao, Wei, Dytso, Alex, Fauß, Michael, Poor, H Vincent. (Finite-Sample Bounds on the Accuracy of Plug-In Estimators of Fisher Information. Entropy, 23 (5), 545 - 545. doi:10.3390/e23050545en_US
dc.description.abstractFinite-sample bounds on the accuracy of Bhattacharya’s plug-in estimator for Fisher information are derived. These bounds are further improved by introducing a clipping step that allows for better control over the score function. This leads to superior upper bounds on the rates of convergence, albeit under slightly different regularity conditions. The performance bounds on both estimators are evaluated for the practically relevant case of a random variable contaminated by Gaussian noise. Moreover, using Brown’s identity, two corresponding estimators of the minimum mean-square error are proposed.en_US
dc.format.extent545 - 545en_US
dc.rightsAuthor's manuscripten_US
dc.titleFinite-Sample Bounds on the Accuracy of Plug-In Estimators of Fisher Informationen_US
dc.typeJournal Articleen_US

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