Generalized estimators, slope, efficiency, and Fisher information bounds

DOI10.1007/s41884-022-00085-7arXiv2208.03630OpenAlexW4311402481MaRDI QIDQ6138793

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Publication date: 16 January 2024

Published in: Information Geometry (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2208.03630

zbMATH Keywords

efficiencyFisher informationslopenon-asymptoticsgeneralized estimators

Mathematics Subject Classification ID

Statistics (62-XX) Nonparametric inference (62Gxx) Foundational topics in statistics (62Axx)

Cites Work

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• Decomposition of Kullback-Leibler risk and unbiasedness for parameter-free estimators
• Maximum likelihood estimators uniformly minimize distribution variance among distribution unbiased estimators in exponential families
• Differential-geometrical methods in statistics.
• Interval estimation for a binomial proportion. (With comments and a rejoinder).
• Variance of the Median of Samples from a Cauchy Distribution
• Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
• Some pioneers of modern statistical theory: a personal reflection
• An Optimum Property of Regular Maximum Likelihood Estimation

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