Modelling Unit Interval COVID-19 Data: An Application of Unit Nadarajah-Haghighi Distribution

Abstract

During the year 2019 and onwards, people from all over the world faced a new deadly and fatal virus named COVID-19. It caused the death of millions of people from all around the world. Since then, scientists have been trying to develop antiviral research and finding appropriate effective medicines. In this research, a new unit interval probability distribution has been proposed to estimate and model the recovery rate of COVID-19. The proposed probability distribution is developed by transforming the variable and named as unit Nadarajah-Haghighi (UNH) distribution. Several statistical properties including reliability measures, quantile function, moments, some entropy measures, order statistics, stress-strength and stochastic ordering have been discussed. Estimation of parameters evaluated by numerical and simulation study. The UNH distribution plays an important role due to its flexibility and variety of shapes. Along with the recovery rate of COVID-19, milk production data is also used to check the usefulness of the UNH distribution. The proposed model is more competitive and flexible as compared to the other unit interval distributions available in the literature. It is necessary to think about strategies, diagnostics, and predicting future factors to lessen the epidemics. At this stage statisticians and policy makers can play an important role in preventing future viral epidemics by estimating and modeling.