Modeling COVID-19 Pandemic Data with New Pareto Model

This paper aims to find a statistical model for modeling the COVID-19 data. We deduced a robust and effective model for fitting the COVID 19 mortality. This model is a new Extended-Pareto distribution (NE-P). The maximum likelihood method is utilized to obtain the estimator of the parameters. A simulation was carried out using different sample sizes and different values of the parameters. In addition, the goodness of fit test statistics was calculated for proposed model compared with the baseline model to find out that our new model is the best for modeling data COVID-19.