E-Bayesian and Hierarchical Bayesian Estimation for the Shape Parameter and Reversed Hazard Rate of Power Function Distribution Under Different Loss Functions

  • E. I. Abdul-SatharEmail author
  • R. B. Athira Krishnan
Research article


This paper presents the E-Bayesian and hierarchical Bayesian estimation of the shape parameter and reversed hazard rate of Power function distribution under the condition that scale parameter is known, based on the different loss functions. We also study some important properties of the proposed estimators. Based on Monte Carlo Simulation study and using a real dataset comparisons are made between the proposed estimators and existing Bayesian estimators. Confidence intervals and coverage probability of the estimators are also computed. From the numerical studies it can be seen that the proposed E-Bayesian and hierarchical Bayesian estimators have better performance when compared to the existing Bayesian estimators in terms of bias and MSE respectively.


E-Bayesian estimation Hierarchical Bayesian estimation Loss function Prior/posterior distribution Reversed hazard rate Credible interval and coverage probability 



The authors would like to thank the Editor in Chief and the reviewers for their constructive comments which helped to improve the quality of the present paper to a great extend.


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Copyright information

© The Indian Society for Probability and Statistics (ISPS) 2019

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of KeralaThiruvananthapuramIndia

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