Neutrosophic Shanker Distribution with Basic Properties and Engineering Applications

In this paper, we develop a new probabilistic model, namely Neutrosophic Shanker Distribution (NSD), which is an extension of the classical Shanker Distribution for data with parameter indeterminacy. The NSD is developed under the framework of neutrosophic statistics, where interval parameters are used to model uncertainties. The basic properties of NSD, such as moments, reliability, hazard rate, and mean residual life, are derived. Estimation procedures for the model parameters using neutrosophic maximum likelihood and moment methods are proposed. The performance of the proposed estimators is evaluated through simulations for various sample sizes, and it is observed that they work satisfactorily. The NSD is applied to real-life problems involving bank waiting times, relief times for patients, and aircraft window strength. The results show that NSD provides better or comparable results compared to other competing models in the class of neutrosophic distributions, namely Neutrosophic Exponential, Neutrosophic Weibull, and Neutrosophic Lindley distributions. The proposed model has immense practical importance in modeling uncertainties in various real-life problems, serving as an effective link between theory and practice. The model also has immense scope for further extension to model censored data and regression data.