Extended log-Kumaraswamy distribution: Its features and application to real-data sets
DOI:
https://doi.org/10.64497/jssci.134Keywords:
log-Kumaraswamy distribution, reliability function, Maximum Likelihood Estimation , New Exponentiated Inverse Weibull distribution; lifetime data analysis; right skewed distribution; survival function; hazard function; maximum likelihood estimation; simulation., momentsAbstract
This study introduces the extended log-Kumaraswamy (ELK) distribution, a flexible statistical model designed to enhance the modeling of diverse datasets, particularly in reliability analysis. Developed using an inverse power transformation, the ELK distribution incorporates additional shape parameters, improving its adaptability compared to traditional distributions. Key properties such as the probability density function, cumulative distribution function, moments, quantile function, and entropy measures are derived and analyzed. The parameters are estimated using various methods of estimations. Simulation studies and real-world applications, such as snowfall and exchange rate datasets, demonstrate the ELK distribution's superior fit compared to competing models. Evaluation metrics like Akaike information criterion (AIC), Bayesian information criterion (BIC), Hannan–Quinn information criterion (HQIC), and consistent Akaike information criterion (CAIC) confirm its efficacy, making it a robust tool for statistical modeling in diverse domains.
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Copyright (c) 2026 Faisal Adamu Idris, Ibrahim Yusuf, Mansur Hassan
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