A Relationship between Classical and Bayesian Estimation Procedures through Fisher Information

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The Bayes estimator demonstrates improved performance as Fisher information increases, suggesting a strong relationship between the two methods.
Simulation studies indicate that the accuracy of parameter estimation enhances significantly when employing Fisher information in both approaches.
Assessment involves the weighted squared error and Kullback-Leibler distance loss functions for the one-parameter exponential distribution model used here as a case study for estimation strategies over datasets from real-world applications .

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This article explores the association between classical and Bayesian estimation techniques using Fisher information, highlighting their implications.

Bhunia et al. (2024) studied this question.

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This article explores the association between classical and Bayesian estimation techniques using Fisher information, highlighting their implications.