Nonlinear regression in COVID-19 forecasting
Scientia Sinica Mathematica
; 51(8):1267-1278, 2021.
Article
in Chinese
| Scopus | ID: covidwho-1456045
ABSTRACT
This paper introduces some kinds of nonlinear growth curves for forecasting cumulative COVID-19 patients. It is shown that the Richards curve is reasonable and flexible in this COVID-19 forecasting. The nonlinear growth curve regression model is established for forecasting cumulative COVID-19 patients and the parameter estimation approach for the model is also given. Specifically, the COVID-19 situation forecasting in China is made well which includes forecasting based on consecutive and piecewise time fitting. It provides a good basis for the future work. © 2021, Science China Press. All right reserved.
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Collection:
Databases of international organizations
Database:
Scopus
Language:
Chinese
Journal:
Scientia Sinica Mathematica
Year:
2021
Document Type:
Article
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