Abstract
In this study, a new family of odd nakagami exponential (NE-G) distributions is introduced and investigated as a new generator of continuous distributions. Quantile, hazard rate function, moments, incomplete moments, order statistics, and entropies are only a few of the statistical features that are investigated. A unique model is presented and thoroughly examined. To estimate model parameters based on describing real-life data sets, the maximum likelihood method is applied. The bias and mean square error of maximum likelihood estimators are investigated using a comprehensive simulation exercise. Finally, the new family adaptability is demonstrated via application to real-world data sets.
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