Estimation Based on Generalized Order Statistics from a Mixture of Two Rayleigh Distributions


  •  Tahani Abushal    
  •  Areej M. AL-Zaydi    

Abstract

This article is concerned with the problem of estimating the parameters, reliability and hazard rate functions of the mixture of two Rayleigh distributions ($MTRD$) based on generalized order statistics ($GOS$). The maximum likelihood and Bayes methods of estimation are used for this purpose. The Markov chain Monte Carlo ($MCMC$) method is used for obtaining the Bayes estimates under the squared error loss and $LINEX$ loss functions. Our results are specialized to progressive Type-II censored order statistics and upper record values. Comparisons are made between Bayesian and maximum likelihood estimators via a Monte Carlo simulation study.


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