Explaining Ovarian Cancer Data with Increasing Hazard Model

Abstract

A single parameter model is developed in this study and used to understand ovarian cancer data. Its several mathematical and statistical properties such as the hazard rate function, moments, moment generating function, mean residual life function, renyi entropy, Bonferroni and Lorenz curve along with order statistics are derived. Maximum likelihood method is used to estimate the parameter. Also the importance of proposed model is checked for engineering data. Analysis reveals that the proposed model has potential to provide a better explanation than several existing lifetime models © 2021 NSP Natural Sciences Publishing Cor.