Extended exp-G family of distributions: Properties, applications and simulation

Abstract

In many applied areas there is a clear need for extended forms of the well-known distributions. Generally, the new distributions are flexible to model real data that present a high degree of skewness and kurtosis. Each of them is applied to solve a particular part of the classical distribution problems. In this paper, the new Extended Exp-G family of distributions is going to be introduced. In particular, G has been considered as the normal distribution and also Weibull distribution. some statistical properties such as moments, Maximum likelihood estimator and regression model have been calculated. The fitness capability of this model has been investigated by fitting this model and others based on real data sets. The maximum likelihood estimators are assessed with simulated real data from proposed model. We present the simulation in order to test validity of maximum likelihood estimators.

Keywords:

• Regression models
• Maximum likelihood
• Moments

Acknowledgment

The authors would like to thank the referees and editors for supplying extremely helpful comments and suggestions.