A Comparison of the Classical Estimators with the Bayes Estimators of One Parameter Inverse Rayleigh Distribution
- Al-Mustansiriya University, Collage of Science, Dept. of Math., Iraq.
- Baghdad University, College of Nursing, Maternal and Child Health Nursing Department, Iraq.
- Baghdad University, College of Administration and Economic, Statistic Department, Iraq.
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In this paper, we obtained the best estimate for the scale parameter (?) of one parameter Inverse Rayleigh distribution, through the comparison of some classical estimators [Maximum Likelihood Estimator (MLE), Uniformly Minimum Variance Unbiased Estimator (UMVUE), and Minimum Mean Squared Error Estimator (MinMSE)[and Bayes estimators under Generalized squared error loss function. In order to get a better understanding of our Bayesian analysis we consider the non-informative prior for ? using Jefferys prior information, as well as informative prior density represented by Exponential distribution. The comparison was based on a Monte Carlo simulation study, on the performance of these estimators with respect to the mean square error (MSE). The results showed that the best estimator for the one parameter Inverse Rayleigh distribution is Bayes estimator under Generalized squared error loss function (when a0 is much greater than a1, and a1 is greater than a2) with Exponential prior when the scale parameter of Exponential prior is less than 1.
Huda A. Rasheed, Siba Zaki Ismail, Asmaa Ghalib Jabir (2015); A Comparison of the Classical Estimators with the Bayes Estimators of One Parameter Inverse Rayleigh Distribution, Int. J. of Adv. Res., 3 (08), 738-749, ISSN 2320-5407. DOI URL: https://dx.doi.org/
