A New Extended G Family of Continuous Distributions with Mathematical Properties, Characterizations and Regression Modeling

Abstract

We propose a new extended G family of distributions. Some of its structural properties are derived and some useful characterization results are presented. The maximum likelihood method is used to estimate the model parameters by means of graphical and numerical Monte Carlo simulation study. The flexibility of the new family illustrated by means of two real data sets. Moreover, we introduce a new log-location regression model based on the proposed family. The martingale and modified deviance residuals are defined to detect outliers and evaluate the model assumptions. The potentiality of the new regression model is illustrated by means of a real data set.