This paper presents a novel generalization of the Akash distribution using the Alpha Power Transformation method, enhancing its flexibility and applicability in statistical modeling. The proposed distribution is systematically examined through an in-depth analysis of its key properties, including moments, skewness, kurtosis, and reliability measures. Its ability to effectively capture skewed data patterns makes it a valuable addition to the family of generalized distributions. Parameter estimation is conducted using both the maximum likelihood and least squares methods to ensure robust inference. The superiority of the proposed model is demonstrated through extensive empirical validation using real-world datasets from medical sciences, where it consistently outperforms existing distributions in terms of goodness-of-fit criteria. The findings underscore the broader applicability of the new distribution in various scientific and engineering domains, offering a powerful tool for researchers and practitioners dealing with asymmetric data.
Rather et al. (Sat,) studied this question.