Marshall-Olkin Sujatha Distribution and Its Applications

Abstract

In this paper, we introduced a two-parameter heavy-tailed, monotone non-increasing hazard rate distribution, and its regression model called the Marshall-Olkin Sujatha (MOS) distribution for life processes.  This study extends the Sujatha distribution using the Marshall-Olkin method and offers a more flexible model for survival data. Some of its useful statistical properties such as the survival rate function, hazard rate function, reversed hazard rate function, cumulative hazard rate function, probability generating function, moment generating function, characteristic function, stochastic ordering, Shannon, and Rényi entropies, heavy-tail property, and order statistics are derived. The study adopted the method of maximum likelihood estimation to estimate the parameters of the proposed model. Simulation studies are carried out to examine the flexibility behavior of the proposed model. The numerical applications and usefulness of the proposed lifetime model are investigated using two real-life data sets. The results obtained show that the proposed model yields the best goodness of fit to all the data sets.