Neutrosophic log-logistic distribution model in complex alloy metal melting point applications

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The log-logistic distribution is more comprehensively applied in the area of survival and reliability engineering analysis for modelling the lifetime data practices of both human and electronic designs. The goal of this paper is to develop a generalization of the classical pattern log-logistic distribution, known as the neutrosophic log-logistic distribution (NLLD), to model various survival and reliability engineering data with indeterminacies. The developed distribution is especially useful for modeling indeterminate data that is roughly positively skewed. This paper discusses the developed NLLD’s main statistical properties such as neutrosophic survival function, neutrosophic hazard rate, neutrosophic moments, and neutrosophic mean time failure. Furthermore, the neutrosophic parameters are estimated using the well-known maximum likelihood (ML) estimation method in a neutrosophic environment. A simulation study is carried out to establish the achievement of the estimated neutrosophic parameters. As a final point, the proposed NLLD applications in the real world have been discussed with the help of real data. The real data illustrated that the efficiency of the proposed model as compared with the existing models.
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Simulation, Neutrosophic statistics, Log-logistic distribution, Neutrosophic Log-Logistic Distribution, NLLD, Maximum likelihood, Indeterminacy, Material engineering, Modeling, Neutrosophic environment
Rao, G. S. (2023). Neutrosophic log-logistic distribution model in complex alloy metal melting point applications. International Journal of Computational Intelligence Systems, 16(1), 48.