Development of Neutrosophic Gamma Distribution for Modeling Neonatal Mortality Data

Abstract

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.  

DOI: 10.5281/zenodo.14644839