Extended Gompertz Distribution: Properties and Estimation under Complete and Censored Data

Abstract

In this paper, a new flexible model with three-parameter alternative to exponential and Gompertz distributions is proposed. Some of its statistical properties are derived including quantities, moments, incomplete moments, moment of residual and reversed residual life. The parameters are estimated using the maximum likelihood method based on complete and Type II right censored data. We assess the performance of estimators in terms of bias and mean square error using simulation study. Finally, three real data sets are analyzed to illustrate the flexibility of the proposed model