Application of a-Sutte model in epidemic prediction - based on software R
Disease Surveillance
; 37(6):802-806, 2022.
Article
in Chinese
| GIM | ID: covidwho-2055475
ABSTRACT
Objective:
To introduce the principle and method ofa-Sutte model, establish a a-Sutte model by using software R, compare the fitting and prediction effects of thea-Sutte model and multiple seasonal autoregressive integrated moving average model, SARIMA model and provides reference for the application of thea-Sutte model in epidemic prediction.
Arima; computer software; coronavirus disease 2019; disease surveys; epidemics; human diseases; machine learning; mathematical models; prediction; viral diseases; man; Severe acute respiratory syndrome coronavirus 2; Brazil; India; Italy; Russia; South Africa; USA; Community of Portuguese Language Countries; high Human Development Index countries; Latin America; America; South America; upper-middle income countries; Commonwealth of Nations; lower-middle income countries; medium Human Development Index countries; South Asia; Asia; European Union Countries; high income countries; Mediterranean Region; OECD Countries; Southern Europe; Europe; very high Human Development Index countries; Homo; Hominidae; primates; mammals; vertebrates; Chordata; animals; eukaryotes; APEC countries; Severe acute respiratory syndrome-related coronavirus; Betacoronavirus; Coronavirinae; Coronaviridae; Nidovirales; positive-sense ssRNA Viruses; ssRNA Viruses; RNA Viruses; viruses; Anglophone Africa; Africa; Southern Africa; Africa South of Sahara; North America; autoregressive integrated moving average; computer programs; disease surveillance; Russian Federation; SARS-CoV-2; subsaharan Africa; United States of America; viral infections
Full text:
Available
Collection:
Databases of international organizations
Database:
GIM
Type of study:
Prognostic study
Language:
Chinese
Journal:
Disease Surveillance
Year:
2022
Document Type:
Article
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