On the Modeling of Two Covid-19 Data Sets Using a Generalized Log-Exponential Transformed Distribution

Abstract

Many papers are being published in many different journals on modeling of Covid-19 data. The vast majority of these papers contributes much to how to handle the epidemic. On the other hand, there have been papers misusing Covid-19 data, for example, simply for mathematical/statistical innovation. In this note, we discuss one such paper where modeling of two data sets of Covid-19 were considered. We show that the data sets can be modeled better by simpler distributions, including the one-parameter exponential distribution. The better fits were shown by the Kolmogorov-Smirnov statistic, its p-value, probability plots and other goodness-of-fit criteria.