Uchenyye zapiski UlGU. Seriya "Matematika i informatsionnyye tekhnologii"
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Uchenyye zapiski UlGU. Seriya "Matematika i informatsionnyye tekhnologii", 2022, Issue 1, Pages 1–7 (Mi ulsu133)  
Forecast and study of time series dependencies on the example of an increase in the incidence of COVID-19

A. A. Butov, A. S. Shabalin

Ulyanovsk State University, Ulyanovsk, Russia
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Abstract: The paper analyzes the dependence of the number of new cases of the SARSCoV-2 virus on the values in previous days. Significant lags for incidence in Russia were identified and an attempt has been made to explain them. Correlograms for different countries are compared. For predict-ing the number of new cases of the disease, a linear regression model is presented as well as the quality criteria that determine this model.
Keywords: time series, autocorrelation function, machine learning, linear regression, covid-19.
Received: 06.04.2022
Revised: 13.05.2022
Bibliographic databases:
Document Type: Article
UDC: УДК 004.942
Language: Russian
Citation: A. A. Butov, A. S. Shabalin, “Forecast and study of time series dependencies on the example of an increase in the incidence of COVID-19”, Uchenyye zapiski UlGU. Seriya “Matematika i informatsionnyye tekhnologii”, 2022, no. 1, 1–7
Citation in format AMSBIB
\Bibitem{ButSha22}
\by A.~A.~Butov, A.~S.~Shabalin
\paper Forecast and study of time series dependencies on the example of an increase in the incidence of COVID-19
\jour Uchenyye zapiski UlGU. Seriya ``Matematika i informatsionnyye tekhnologii''
\yr 2022
\issue 1
\pages 1--7
\mathnet{http://mi.mathnet.ru/ulsu133}
\elib{https://elibrary.ru/item.asp?id=48735614}
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