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Neutrosophic Sets and Systems

Abstract

The exponential distribution is a widely used lifetime model with applications spanning numerous disciplines. The DUS transformation extends the applicability of the exponential distribution by improving its flexibility for diverse real-world scenarios. This study proposes the Neutrosophic DUS Exponential Distribution (NDUS-ED), an extension of the DUS Exponential Distribution, designed to effectively address and quantify uncertainty, inconsistency, and indeterminacy in data. Key statistical properties of NDUS-ED, including quantiles, moments, moment-generating functions, and order statistics, are derived under neutrosophic conditions. The performance of estimated parameters is evaluated through simulation, revealing superior results with larger sample sizes, particularly in managing imprecise and indeterminate data. Finally, the proposed distribution is applied to an actual dataset, and the results are compared with those of the Neutrosophic Exponential Distribution and the DUS Exponential Distribution, demonstrating superior performance.

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