EXAMINING THE GENERALIZED ODD LOG-LOGISTIC FAMILY: A REGRESSION COMPILATION.
Bimodality. Diagnostic. Extreme events. Generalized odd log-logistic family. Maximum likelihood. Regression model. Residual. Simulation.
In this work, considering the new family of distributions, generalized odd log-logisticG, several applications were proposed with different real data using regression models. The distributions in this family accommodate asymmetric, bimodal and fat tail shapes, showing flexibility when compared to other generators. Based on the new generating family of distributions, regression models were introduced with distinct systematic structures and all the computational modeling is implemented via R software. The results obtained using complex data sets demonstrated that the proposed models are a viable alternative to competing distributions and corroborate previous studies.