Kumaraswamy Inverted Topp–Leone Distribution with Applications to COVID-19 Data

In this paper, an attempt is made to discover the distributionof COVID-19 spread in different countries such as;Saudi Arabia, Italy,Argentina and Angola by specifying an optimal statistical distribution for analyzing the mortality rate of COVID-19. A new generalization of the recentlyinverted Topp Leone distribution, called Kumaraswamy inverted Topp–Leonedistribution, is proposed by combining the Kumaraswamy-G family and theinverted Topp–Leone distribution. We initially provide a linear representationof its density function. We give some of its structure properties, such as quantile function, median, moments, incomplete moments, Lorenz and Bonferronicurves, entropies measures and stress-strength reliability. Then, Bayesian andmaximum likelihood estimators for parameters of the Kumaraswamy invertedTopp–Leone distribution under Type-II censored sample are considered.Bayesian estimator is regarded using symmetric and asymmetric loss functions. As analytical solution is too hard, behaviours of estimates have beendone viz Monte Carlo simulation study and some reasonable comparisonshave been presented. The outcomes of the simulation study confirmed theefficiencies of obtained estimates as well as yielded the superiority of Bayesianestimate under adequate priors compared to the maximum likelihood estimate.Application to COVID-19 in some countries showed that the new distributionis more appropriate than some other competitive models.