Modified Logistic Lomax Distribution: Model, Properties, Simulation, and Application to real dataset

Abstract

We have introduced Modified Logistic Lomax (MLL) Distribution Modifying the Logistic Lomax model. Modification of the model makes it to give different shaped density curve and hazard rate curves enabling model more flexible and suitable for various type of the datasets. Study of various statistical properties and Simulation study is performed. The MLL model is more useful for real datasets where classical probability models do not analyze the dataset appropriately. Maximum likelihood estimation (MLE), Least square estimation (LSE) and Cramer-von Mises methods (CVM) are used for parameter estimation and consistent results of the parameters are
seen. Information criterion and graphical approach demonstrate the superiority of the model over some probability models. The MLL model may be helpful for the researcher to know the formulation of the new probability model and its application for real data analysis. All the computation analysis is performed using R programming.