Neutrosophic exponentiated inverse Rayleigh distribution: Properties and Applications

Abstract

In the field of survival analysis, the exponentiated inverse Rayleigh distribution is used to simulate lifetime data practices of human. In order to describe diverse survival data with indeterminacies, this work aims to create a generalization of the traditional pattern exponentiated inverse Rayleigh distribution, referred to as the neutrosophic exponentiated inverse Rayleigh distribution (NEIRD). In particular, modeling uncertain data that is roughly positively skewed makes use of the established distribution. The key statistical characteristics of the developed NEIRD, such as the neutrosophic survival function, neutrosophic hazard rate and neutrosophic moments, are discussed in this study. Additionally, in a neutrosophic well-known maximum likelihood estimation approach is used to estimate the neutrosophic parameters. A simulation study is conducted to determine whether the estimated neutrosophic parameters were achieved. Last but not least, real data has been used to discuss the potential NEIRD applications in the real world. The effectiveness of the suggested model in comparison to the existing distributions was demonstrated by real data.