On the Coronavirus Disease Death Rate Modeling Utilizing Generalized Exponential Kumaraswamy

Abstract

This paper aims to model COVID-19 in different countries, including Iran, Canada, Italy, and Mexico. A novel five-parameter lifetime distribution termed the Odd generalized exponential Kumaraswamy-inverse exponential distribution (OEKIE) is presented by combining the Kumaraswamy-inverse exponential distribution with the odd generalized exponential generator. The theoretical features of the new distribution, as well as its reliability functions, moments, and order statistics are investigated. The novel distribution has numerous advantages, since its density has a variety of symmetric and asymmetric forms. Furthermore, The graphs of the hazard rate function exhibit various asymmetrical shapes such as decreasing, increasing, upside-down bathtub shapes, and inverted J-shapes making OEKIE suitable for modeling hazards behaviors more likely to be observed in practical settings like human mortality, and biological applications. The OEKIE’s parameters are estimated using the maximum likelihood approach. The effectiveness of OEKIE is demonstrated through both numerical study and applications to four COVID-19 mortality rate data sets. The OEKIE provides best fits to COVID-19 data compared to other extended forms of the Kumaraswamy and inverse exponential distributions which may attract wider applications in different fields.