Comparison of Approximate Bayes Estimators under different loss functions for Parameters of Odd Weibull Distribution

Abstract

In this study, it is compared the performances of Maximum Likelihood (ML) and Bayes estimators under different loss functions for parameters of odd weibull distribution. ML estimators is computed by using Newton Raphson method. Approximate Bayes estimators by means of Tierney Kadane Approximation under Squared Error, Linex and General Entropy loss functions by using Jefrey’s extension prior is obtained. For different sample sizes, ML and Bayes estimators are compared in terms of mean square errors using a Monte Carlo simulation study.