Power Xgamma distribution: properties, estimation, regression, simulation and applications - Okechukwu Obulezi; Precious Ibeakuzie; Ifeanyi Anabike; Chinyere Igbokwe; Harrison Etaga (Computational Algorithms and Numerical Dimensions)
In this study, an extension of Xgamma distribution has been proposed and studied. The extension has an additional parameter accounting for the shape of the distribution. The properties of the proposed distribution were derived and discussed. The estimation of the parameters was done using the maximum likelihood method. The study’s uniqueness is in developing a parametric regression model capable of competing with the classical regression model and also useful in the face of censored data. The applicability and flexibility were demonstrated using simulation studies and some lifetime data.