Quasi-E-Bayesian criteria versus quasi-Bayesian, quasi-hierarchical Bayesian and quasi-empirical Bayesian methods for estimating the scale parameter of the Erlang distribution

  • Authors

    • Hesham Reyad Lecture in EL Qassim University
    • Adil Younis Professor in Sudan University of Science and Technology
    • Amal Alkhedir Assistant of professor in Sudan University of Science and Technology
    2016-05-10
    https://doi.org/10.14419/ijasp.v4i1.6095
  • Erlang Distribution, Quasi-Bayes Estimates, Quasi-E-Bayeses Estimates, Quasi-Empirical Bayes Estimates, Quasi-Hierarchical Bayes Esti-mates.

  • This paper proposes a new modification for the E-Bayesian method of estimation to introduce a new technique namely Quasi E-Bayesian method (or briefly QE-Bayesian). The suggested criteria built in replacing the likelihood function by the quasi likelihood function in the E-Bayesian technique. This study is devoted to evaluate the performance of the new method versus the quasi-Bayesian, quasi-hierarchical Bayesian and quasi-empirical Bayesian approaches in estimating the scale parameter of the Erlang distribution. All estimators are obtained under symmetric loss function [squared error loss (SELF))] and four different asymmetric loss functions [Precautionary loss function (PLF), entropy loss function (ELF), Degroot loss function (DLF) and quadratic loss function (QLF)]. The properties of the QE-Bayesian estimates are introduced and the relations between the QE-Bayes and quasi-hierarchical Bayes estimates are discussed. Comparisons among all estimators are performed in terms of mean square error (MSE) via Monte Carlo simulation.

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