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Modeling and fitting for heteroscedastic time-series data of infectious diseases / 中华疾病控制杂志
Article in Chinese | WPRIM (Western Pacific) | ID: wpr-547602
Responsible library: WPRO
ABSTRACT
Objective To explore the application of heteroscedastic time series model to the analysis of data of infectious diseases.Methods ARIMA and AR-GARCH models were used to fit the incidence of gonorrhea.Results The time series in this study,which was heteroscedastic significantly,finally was well fitted by AR(1)-GARCH(0,1) model through model selecting.Conclusions AR-GARCH model is suitable for analyzing heteroscedastic time-series data of infectious diseases.

Full text: Available Database: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Disease Control & Prevention Year: 2009 Document type: Article
Full text: Available Database: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Disease Control & Prevention Year: 2009 Document type: Article
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