Comparison of the Suggested loss Function with Generalized Loss Function for One Parameter Inverse Rayleigh Distribution
Keywords:
Inverse Rayleigh Distribution, Bayes estimator, Suggested loss function(SLF), Generalized Loss Function(GLF), Maximum likelihood (MLE), Jeffery prior; Exponential informative prior MSE.Abstract
The experiences in the life are considered important for many fields, such as industry, medical and others. In literature, researchers are focused on flexible lifetime distribution.
In this paper, some Bayesian estimators for the unknown scale parameter of Inverse Rayleigh Distribution have been obtained, of different two loss functions, represented by Suggested and Generalized loss function based on Non-Informative prior using Jeffery's and informative prior represented by Exponential distribution. The performance of estimators is compared empirically with Maximum Likelihood estimator, Using Monte Carlo Simulation depending on the Mean Square Error (MSE). Generally, the preference of Bayesian method of Suggested loss function with Exponential informative prior are the best estimator compared to others.
