Master’s Thesis at the University of Basrah Discusses Estimation of the Suga Survival Function
A master’s thesis at the College of Administration and Economics, University of Basrah, explored “Some Bayesian Genetic Estimators in Estimating the Survival Function of the Exponential Inverse Suga Distribution.”
The thesis, presented by researcher Rahma Abdul-Zahra Matar, aimed to propose a probabilistic model for the Exponential Inverse Suga Distribution (EISD) and to estimate the survival function of the proposed distribution using one of the most important artificial intelligence algorithms.
The study included an evaluation of the estimation methods applied to estimate the survival function through a Monte Carlo simulation study.
The thesis concluded with the superiority of the proposed distribution (EISD) in effectively representing such data.
Department of Media and Governmental Communication
