Development of Neutrosophic Gamma Distribution for Modeling Neonatal Mortality Data

This study explores and investigates the key characteristics of the neutrosophic gamma model (NGM) to analyze neonatal mortality data. The proposed model has the ability to handle imprecision, vagueness and uncertainty in data which often exist in health statistics. The key characteristics of the proposed model such as the probability density function, cumulative distribution function, statistical moments and some basic shape coefficients are discussed to clarify its difference from the classical model. Air pollution mortality data are commonly encountered imprecise and incomplete information due to factors such as missing values, measurement errors, reporting inconsistencies. The proposed NGM has the inherent ability to model such ambiguous data as robust tool for addressing these challenges. Through a detailed statistical analysis of mortality data linked to air pollution in Saudi Arabia, we demonstrate that the NGM outperforms traditional models in managing uncertainty and providing more accurate mortality analysis. This study not only enhances the theoretical structure of the NGM but also provides practical implications for policy formulation and healthcare management.