Okechukwu Obulezi - Department of Statistics, Faculty of Sciences, Nnamdi Azikiwe University, Awka, Nigeria.
Precious Ibeakuzie - Department of Statistics, Faculty of Sciences, Nnamdi Azikiwe University, Awka, Nigeria.
Ifeanyi Anabike - Department of Statistics, Faculty of Sciences, Nnamdi Azikiwe University, Awka, Nigeria.
Chinyere Igbokwe - Department of Statistics, School of Science and Industrial Technology, Abia State Polytechnic, Aba, Nigeria.
Harrison Etaga - Department of Statistics, Faculty of Sciences, Nnamdi Azikiwe University, Awka, Nigeria.

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.

Power Xgamma distribution, COVID-۱۹ Patients, CD۴ count, HIV/AIDS, Log-transformation, parametric regression