Title : ( Sibling rivalry within inverse Weibull family to predict the COVID-19 spread in South Africa )
Authors: Farzane Hashemi , Andriette Bekker , Kirsten Smith , Mohammad Arashi ,
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Abstract
This article draws attention to a comparative study of different members within the inverse Weibull Power Series (IWPS) to analyze the COVID-19 data from South Africa for the period from 27 March to 23 August 2020. A new sibling of the IWPS is introduced, namely the inverse Weibull negative binomial. An EM algorithm is developed for computing the maximum likelihood estimates of the model parameters. The IWPS growth curve model and its special cases are used for prediction of the COVID-19 spread in South Africa. It is found that the IWPS model fits the disease growth of the COVID-19 confirmed cases well with worthy long-term predictions. The IWPS growth curve modeling of South African predicts that the number of confirmed new cases will decrease at the end of November 2020.
Keywords
, Confirmed cases; COVID, 19; growth curve; IWPS; prediction; South African
@article{paperid:1089224,
author = {Farzane Hashemi and Andriette Bekker and Kirsten Smith and Arashi, Mohammad},
title = {Sibling rivalry within inverse Weibull family to predict the COVID-19 spread in South Africa},
journal = {Communications in Statistics: Case Studies, Data Analysis and Applications},
year = {2022},
volume = {8},
number = {1},
month = {January},
issn = {2373-7484},
pages = {119--132},
numpages = {13},
keywords = {Confirmed cases; COVID-19; growth curve; IWPS; prediction; South African},
}
%0 Journal Article
%T Sibling rivalry within inverse Weibull family to predict the COVID-19 spread in South Africa
%A Farzane Hashemi
%A Andriette Bekker
%A Kirsten Smith
%A Arashi, Mohammad
%J Communications in Statistics: Case Studies, Data Analysis and Applications
%@ 2373-7484
%D 2022
