**6. Discussion**

The *OGE2-G* class of distribution is proposed and studied with some mathematical properties such as ordinary and incomplete moments, mean deviations and generating functions. The maximum likelihood approach is used to estimate the model parameters. Then, we focussed our attention to one of the special member of the family defined with the Fréchet distribution, called the OGE2Fr distribution. We established the optimized maximum likelihood methodology in particular, with the goal of effectively estimating model parameters and validated their convergence by a simulation study, ensuring that the projections have asymptotic properties. To demonstrate the potentiality of the proposed model, two applications to real data sets are provided. The creation of various regression models, Bayesian parameter estimates, and studies of new data sets will all be part of a future effort. We feel that the OGE2-G family can be useful for professionals in statistical analyses beyond the scope of this research because of its several other features.

**Author Contributions:** Conceptualization: S.K. and M.H.T.; Methodology: W.A.; Software: O.S.B.; Validation: M.H.T., W.A. and A.A.A.; Formal analysis: S.K.; Investigation: S.K.; Resources: M.H.T.; Data curation: O.S.B. and W.A.; Writing—original draft preparation:, S.K.; Writing—review and editing: S.K.; Visualization: S.K.; Supervision: A.A.A.; Project administration: O.S.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This manuscript is supported by Digiteknologian TKI-ymparisto project A74338(ERDF, 357 Regional Council of Pohjois-Savo.

**Data Availability Statement:** https://data.world/datasets/insurance/ (accesed on 28 June 2021).

**Acknowledgments:** The authors would like to thank the reviewers for their thoughtful remarks and recommendations, which considerably enhanced the paper's presentation.

**Conflicts of Interest:** The authors state that they have no conflicting interests to declare in this work.
