Bayes approach to study shape parameter of Frechet distribution

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    In this paper, Frechet distribution under Bayesian paradigm is studied. Posterior distributions are derived by using Gumbel Type-II and Levy prior. Quadrature numerical integration technique is utilized to solve posterior distribution. Bayes estimators and their risks have been obtained by using four loss functions. Prior predictive distributions are derived for elicitation of hyperparameters. The performance of Bayes estimators are compared by using Monte Carlo simulation study.


  • Keywords


    Informative Prior; Bayes Estimates; Posterior Risks; Loss Functions; Elicitation; Monte Carlo simulation.

  • References


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Article ID: 4644
 
DOI: 10.14419/ijbas.v4i3.4644




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