Statistical Characterization of the Neutrosophic Moyal Distribution

The Moyal distribution is widely utilized in various fields due to its effectiveness in modeling heavy-tailed processes, such as ionization losses and certain risk assessments. In this work, we present a neutrosophic version of the Moyal distribution that extends the classical Moyal distribution while incorporating uncertainty and imprecision associated with its parameters. To better explore the neutrosophic structure, we provide the detailed derivation of some essential mathematical characteristics concerning all the properties that this distribution possesses. The proposed neutrosophic Moyal (NM) model is the one that allows it to work very well in situations where data is vague or undetermined. The proposed neutrosophic model can be effectively adopted when the Moyal distribution parameters are known and lie in the range or interval. We also develop the quantile function of the proposed model under an uncertain environment. A simulation study has been carried out to assess the adequacy of neutrosophic quantile function. Numerical results demonstrate that quantile function is quite efficient in terms of generating neutrosophic random data from the proposed model.