A new extended rayleigh distribution with applications of COVID-19 data

• Published in: Results in physics Vol. 23; p. 104012
• Main Authors: Almongy, Hisham M., Almetwally, Ehab M., Aljohani, Hassan M., Alghamdi, Abdulaziz S., Hafez, E.H.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.04.2021; The Authors. Published by Elsevier B.V; Elsevier
• Subjects: 60E05; 62F10; Bayesian; COVID-19; Extended odd Weibull family; Maximum product spacing; Rayleigh distribution; Extended odd Weibull family; COVID-19; Bayesian; 62F10; Rayleigh distribution; Maximum product spacing; 60E05
• ISSN: 2211-3797; 2211-3797
• DOI: 10.1016/j.rinp.2021.104012

This paper aims to model the COVID-19 mortality rates in Italy, Mexico, and the Netherlands, by specifying an optimal statistical model to analyze the mortality rate of COVID-19. A new lifetime distribution with three-parameter is introduced by a combination of Rayleigh distribution and extended odd Weibull family to produce the extended odd Weibull Rayleigh (EOWR) distribution. This new distribution has many excellent properties as simple linear representation, hazard rate function, and moment generating function. Maximum likelihood, maximum product spacing and Bayesian estimation methods are applied to estimate the unknown parameters of EOWR distribution. MCMC method is used for the Bayesian estimation. A numerical result of the Monte Carlo simulation is obtained to assess the use of estimation methods. Also, data analysis for the real data of mortality rate is considered.