A New Generalized-$X$ Family for Analyzing the COVID-19 Data Set: a Case Study

Abstract

Nowadays, researchers in applied sectors are highly motivated to propose and study new generalizations of the existing distributions to provide the best fit to data. To provide a close fit to data in numerous sectors, a series of new distributions have been proposed. In this study, we propose a new family called the new generalized- X (for short, “NG- X ”) family of distributions. Based on the NG- X method, a novel modification of the Weibull model called the new generalized-Weibull (for short, “NG-Weibull”) distribution is studied. The heavy-tailed characteristics of the NG- X distributions are derived. The maximum likelihood estimators of the NG- X distributions are also obtained. Based on the special case (i.e., NG-Weibull) of the NG- X family, a simulation study is provided. The practical performance of the new NG-Weibull model is assessed by analyzing the COVID-19 data set. The fitting results of the NG-Weibull model are compared with three other competing models. Based on certain statistical measures, it is observed that the NG-Weibull model is the best competitive model.

A novel flexible exponent power-X family of distributions with applications to COVID-19 mortality rate in Mexico and Canada

“…int/]. For mor details about the DS 1, we refer to Almetwally et al 31 , and Xin et al 32 Corresponding to DATS 1, the numerical values of MLEs along with standard errors enclosed in parenthesis of the NFEP-Wei and rival distributions (i.e., φMLE , αMLE , δMLE , âMLE , bMLE ) are recorded in Table 4. Furthermore, the numerical values of the goodness of fit measures of the NGEP-Wei and other competitive rival distributions are recorded in Table 5.…”