Classical Methods to Estimate the Parameters of Exponentiated Weibull Distribution

Abstract

In this article the Exponentiated Weibull distribution with some of its properties is considered. Classical methods, Maximum likelihood estimator method, ordinary least squares estimator method and rank set sampling estimator method are proposed to estimate all the unknown parameters (β,Ψ,θ) of the distribution. Newton–Raphson method is used to solve the above three methods, simulation procedure is used to generated some sample sizes and finally mean squares error measure are used to compare between them. We find Maximum likelihood estimator method has the smallest mean square error.

Estimation of the Parameters by Using non-Bayesian in Modified Weibull Extension Distribution

“…In 2019, Al Kanani and Jalil [2] discussed some estimation method for new distribution (mixture distribution) to estimate the parameters. In 2021, Al Kanani and Ali [1] dealing with exponentiated Weibull as a special case of Weibul distributions for estimate the parameters. By the way, the aim of this research is estimating all the three parameters of the modified Weibull extension model, by using maximum likelihood estimator method, and ordinary least squares estimator method to show the best values of parameters.…”