Bayesian and Non-Bayesian Estimation for the Parameter of Bivariate Generalized Rayleigh Distribution Based on Clayton Copula under Progressive Type-II Censoring with Random Removal

Abstract

In this paper, the bivariate generalized Rayleigh distribution is introduced based on Clayton copula and denoted as (Clayton-BGR). The likelihood function for progressive Type-II censoring scheme with random removal is derived and applied on the Clayton-BGR distribution. Bayesian and non -Bayesian estimation methods based on progressive Type-II censoring have been discussed. Asymptotic confidence intervals and bootstrap confidence intervals for the unknown parameters are obtained. Also, a simulation study has been conducted to compare the performances between censoring schemes. Also, two real data sets are analyzed to investigate the models and useful results are obtained for illustrative purposes.

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Correspondence to Ehab M. Almetwally.

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El-Sherpieny, ES.A., Almetwally, E.M. & Muhammed, H.Z. Bayesian and Non-Bayesian Estimation for the Parameter of Bivariate Generalized Rayleigh Distribution Based on Clayton Copula under Progressive Type-II Censoring with Random Removal. Sankhya A (2021). https://doi.org/10.1007/s13171-021-00254-3

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Keywords

  • Bivariate generalized Rayleigh
  • Clayton copula
  • Maximum likelihood estimation
  • Bayesian estimation
  • Progressive type-II censoring
  • Bootstrap confidence interval