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Research Article Open access CC BY 4.0

A Power Gompertz Distribution: Model, Properties and Application to Bladder Cancer Data

Terna Godfrey Ieren, Felix M. Kromtit, Blessing Uke Agbor, Innocent Boyle Eraikhuemen, Peter Oluwaseun Koleoso

Asian Research Journal of Mathematics · pp. 1–14 · Published 19 Oct 2019

10.9734/arjom/2019/v15i230146

Abstract

This paper uses a power transformation approach to introduce a three-parameter probability distribution which gives another extension of the Gompertz distribution known as “Power Gompertz distribution”. The statistical features of the power Gompertz distribution are systematically derived and studied appropriately. The three parameters of the new model are being estimated using the method of maximum likelihood estimation. The proposed distribution has also been compared to the Gompertz distribution using a real life dataset and the result shows that the Power Gompertz distribution has better performance than the Gompertz distribution and hence will be more useful and effective if applied in some real life situations especially survival analysis and cure fraction modeling just like the conventional Gompertz distribution.

Power transformation Gompertz distribution statistical properties parameters method of maximum likelihood estimation real life data performance.

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