DUS Inverse Weibull Distribution and Parameter Estimation in Regression Model

This paper considers various estimation methods to estimate the unknown parameters of the DUS Inverse Weibull insert ignore into journalissuearticles values(DIW); distribution using the maximum likelihood insert ignore into journalissuearticles values(ML);, least squares insert ignore into journalissuearticles values(LS);, weighted least squares insert ignore into journalissuearticles values(WLS);, Cramer-von Mises insert ignore into journalissuearticles values(CVM); and the Anderson-Darling insert ignore into journalissuearticles values(AD); estimators. A Monte-Carlo simulation study is conducted to determine the most preferable estimators in terms of their efficiencies. Furthermore, the distribution of the error terms in the simple linear regression is assumed to be DIW to show the implementation of it to the linear models. We also carry out a simulation study for comparing the performances of the estimators of the unknown regression parameters.