A Bayesian variation of Basu's theorem and its ramification in statistical inference
One of the celebrated results of Professor D. Basu is his 1955 paper on ancillary statistics, which established the well known Basu’s Theorem. A Bayesian version of this result, where the parameter Θ is treated as a random variable, is developed in this note, along with other extensions of the related classical results, such as Rao-Blackwell and Lehmann-Scheffe theorems and the relation between complete sufficiency and minimal sufficiency. These extensions shed new lights on these fundamental theorems for frequentist statistical inference in the context Bayesian inference.
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s13171-023-00334-6
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Work Title | A Bayesian variation of Basu's theorem and its ramification in statistical inference |
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License | In Copyright (Rights Reserved) |
Work Type | Article |
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Publication Date | December 22, 2023 |
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Deposited | March 05, 2024 |
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