Conditions for interior based constrained prior distributions to ensure probability density

Document Type : Original Scientific Paper

Authors

1 Department of Statistics‎, ‎Amirkabir University of Technology‎, ‎Tehran‎, ‎Iran

2 Department of Mathematics‎, ‎Kharazmi University‎, ‎Tehran‎, ‎Iran

Abstract

In Bayesian inference‎, ‎the acquisition of prior distributions plays a fundamental role‎. ‎While authorized priors need not conform to traditional probability densities and may be improper priors‎, ‎obtaining proper prior densities remains a challenge in the Bayesian literature‎. ‎This article explores a set of conditions that enable the establishment of specific assumptions‎, ‎ensuring that maximum entropy priors and restricted reference priors become proper and transform into probability density priors‎. ‎By examining these conditions‎, ‎this study contributes to the advancement of proper prior acquisition in Bayesian analysis.

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References

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Journal of Statistical Modelling: Theory and Applications
Volume 3, Issue 2
July 2022
Pages 145-155

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History

  • Receive Date: 05 August 2023
  • Revise Date: 10 September 2023
  • Accept Date: 16 November 2023

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