Marshall Olkin exponential Gompertz distribution: Properties and applications

Abstract

Generalizing distribution is an important area in probability theory. Many distributions are not suitable for modeling data, that are either symmetric or heavily skewed. In this paper, a new compound distribution termed as Marshall Olkin Exponential Gompertz (MOEGo) is introduced. Several essential statistical properties of MOEGo distribution were studied and investigated. The estimation of distribution parameters was performed using the maximum likelihood estimation method. Two real data (symmetric and right-skewed) were adopted to illustrate the flexibility of MOEGo distribution. This flexibility enables the use of MOEGo distribution in various application areas.