Nonlinear Statistical models for COVID-19 fourth wave cases in Egypt | ||||
| مجلة الدراسات التجارية المعاصرة | ||||
| Volume 9, Issue 15, January 2023, Page 330-346 PDF (715.61 K) | ||||
| Document Type: المقالة الأصلية | ||||
| DOI: 10.21608/csj.2023.286227 | ||||
 View on SCiNiTO | ||||
| Author | ||||
مها توفيق 
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| کلية التجارة جامعة طنطا | ||||
| Abstract | ||||
| Abstract This study aimed to apply the nonlinear models (Gompertz, Richards’, and Weibull) that enables us to study and forecast the daily number of COVID-19 cases in Egypt and determine which of them is the suitable to describe the data of COVID-19 fourth wave cases during the period from 28th of July, 2021 to 5 th January, 2022.The models’ parameters were estimated, and the Comparison of these models’ fits was made using some statistics (F-test,R^2, AIC, BIC, AICc, and MAPE). Applied on “nonlinear regression” tool available in SPSS-26, and Microsoft excel 2016. According to the highest F and R^2, and lowest values for RMSE, Bias, MAE, AIC, BIC, and AICc, the results indicate that the Weibull model is the best adequate model for studying the daily number of COVID-19 cases in Egypt. The proposed Weibull model is statistically significant for describing the study data. In this study, the growth curve of real data sets (the daily number of fourth wave COVID-19 cases in Egypt) was examined using three sigmoidal growth models (Gompertz, Richards, and Weibull). | ||||
| Keywords | ||||
| Weibull model; Gompertz model; Richards’ model | ||||
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