Abstract
In this paper, we propose a new version of the Gumbel Distribution using a sine technique family. We discuss the key properties of this distribution, such as the probability density function, the cumulative distribution function, the survival function, the hazard function, the cumulative hazard, and the moments. Additionally, we present a method for estimating the distribution's parameters. We then analyze a dataset using the original and generalized distributions, comparing the results and using goodness-of-fit measures to determine which distribution best fits the data. Finally, we provide conclusions based on our findings, with many examples and valid comparisons applied on fuzzy data.
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