A two-parameter class of generator named the alpha power Topp-Leone-G (APTL-G) distribution for generating and engendering up to the minute family of continuous contemporary distributions is proposed. The propounded model has a bathtub and J-shapes hazard rate characteristics in data science. Thus, it has enhanced data analysis because of its productivity. A weighted function of the parent distribution was used to obtain the quantile function for the different sub-models considered. The record values of the differences of the lower and upper values were obtained in a closed-form to enable its applicability. The APTL-G model parameters values were captured and obtained in their simplified cases by the maximum likelihood approach. A simulation was also adopted to examine and investigate the performance, productivity, efficiency and tractability of the APTL-G sub-models. The outcomes of the real-life application and simulation study show that the performance of the goodness-of-fit of the APTL-G model is more flexible and tractable with real-life data sets concerning its goodness-of-fit.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234606PMC
http://dx.doi.org/10.1016/j.heliyon.2022.e09775DOI Listing

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