EXPONENTIATED GENERALIZED BURR XII DISTRIBUTION: PROPERTIES AND APPLICATIONS

Abstract

This study introduces a new four-parameter distribution, the Exponentiated Generalized Burr XII (EGBXII) distribution. The model was developed by combining the classical Burr XII distribution with the Exponentiated Generalized family, offering enhanced flexibility. Its probability density function (pdf) exhibits desirable features, including unimodal and inverted bathtub shapes. The hazard rate function can represent both increasing and decreasing patterns, making it versatile for modeling diverse real-world phenomena. Key properties of the distribution, such as moments, the moment-generating function, skewness, and kurtosis, are derived. The parameters of the distribution were estimated using the maximum likelihood method. A simulation study was conducted to evaluate the behavior of these estimated parameters. Finally, the proposed model was applied to two real-world datasets, where it demonstrated superior performance in terms of efficiency and consistency compared to other existing models, as evaluated using comparative criteria, including Akaike information Criterion (AIC), Bayesian information criterion (BIC), Hannan Quinn information criterion (HQIC), Corrected Akaike Information Criterion (CAIC), and the Kolmogorov-Smirnov (KS) test.