A New Family of Distributions with an Application to Exponentially Distribution

Abstract

This paper introduces a new continuous distribution family called the Alpha logarithm family, which is a new modelling strategy for fitting data subject to univariate continuous distributions. This is achieved by introducing an additional parameter for greater flexibility using a single-parameter Natural logarithm transformation which can enhance some of the modeling capabilities of some Parental Continuous Distributions: This technique was applied to the exponential distribution to obtain a new two-parameter distribution, and the changes that occurred in the exponential distribution were observed. The general properties and functions of the new distribution were also derived and studied, and the estimators of the two parameters were derived. The efficiency of the estimators is verified through the simulation study. The new distribution is also applied to two sets of real data to prove the benefit of the new transformation, and we show that the proposed model is better than the asymptotic distributions with which it was compared on the selected data.