A new improved form of the Lomax model: Its bivariate extension and an application in the financial sector

Abstract

The Lomax model, also known as Pareto Type-II, has broad feasibility, especially in financing. This work introduces a new generalization of the Lomax model called the arc-sine exponentiation Lomax, which helps consider economic phenomena. The arc-sine exponentiation Lomax distribution captures a variety of shapes of density and hazard functions. The estimators of the proposed model’s parameters are derived using the maximum likelihood method. In a simulation study, the accuracy and efficacy of estimators are evaluated by computing their mean square errors and biases.Furthermore, a bivariate extension of the arc-sine exponentiation Lomax model is also introduced. The bivariate extension is introduced using Farlie–Gumble–Morgenstern copula approach. The new bivariate model is called Farlie–Gumble–Morgenstern arc-sine exponentiation Lomax distribution. Finally, a data set of thirty-two observations representing the export of goods demonstrates the arc-sine exponentiation Lomax model. The best-fitting results of the arc-sine exponentiatial Lomax are compared with some prominent extensions of the Lomax distribution.