Survival Function Estimation for Fuzzy Gompertz Distribution with neutrosophic data

Abstract

A relatively recent area of research known as neutrosophic statistics deals with data that are ambiguous, indeterminate, and inconsistent. By embracing the idea of neutrosophy, which denotes the existence of three components in a statement: truth, falsity, and indeterminacy, it broadens the application of classical statistics. One of the significant offshoots of statistics is life-time data analysis. Traditional statistical methods only account for variation within the data and calculate lifetime observations as accurate numbers. Actually, there are two different kinds of uncertainty in data: fluctuation between observations and fuzziness. As a result, analysis techniques that solely employ precise lifetime data and ignore fuzziness use incomplete information and produce false results. This paper sought to generalize hazard rates, survival functions, and parameter estimates for fuzzy Gompertz Distribution. Simulation studies are implemented to examine the performance of the fuzzy Gompertz Distribution. The results show that the fuzzy Gompertz Distribution has better flexibility in handling over the standard Gompertz Distribution.