A Parametric Regression Model using Power Chris-Jerry Distribution with Application to Censored Data

Abstract

    The interdependency of various areas of Statistics is gaining good attention in the literature. This is possible through innovations such as the log-transformation of distribution to a parametric regression model hence integrating contemporary probability distribution models with the classical regression method. The new model is essentially preferred due to its applicability in wider scenarios. In this article, the base distribution is the Power Chris-Jerry distribution. The reparametrized regression model equivalent was carefully derived with the maximum estimation procedure under censored sample also considered. A simulation study of the log-power Chris-Jerry regression model was carried out with measures of performance presented. The COVID-19 patient lifetime censored data was deployed to justify the motivation for developing the new model and twelve competing models were used to compare the proposed regression. The results show that the proposed model is indeed better and preferred to its competitors.

Keywords

• corruption perception index
• gross domestic product
• real gross domestic product
• nigeria economy
• transparency international
• treasury single account