A New Model of Exponentiated Generalized Transmuted G Family of Distributions With Real Data Applications

In this paper, a new family of distributions is introduced which generalized many families of distributions in literature. The distribution function of the new family of distributions is constructed using the exponentiated generalized transmuted family of distributions given in literature. Some useful properties of the new family of distributions are introduced. Estimation of the parameters of the new family of distributions is introduced using the maximum likelihood method. A simulation study is introduced to estimate the parameters of exponentiated generalized transmuted exponential distribution. A real data application that represents bladder cancer data is introduced to compare exponentiated generalized transmuted Weibull distribution with some other distributions. Another real data represent that the COVID‐19 data in Saudi Arabia are introduced to obtain results for exponentiated generalized transmuted exponential distribution.