Modeling and fitting for heteroscedastic time-series data of infectious diseases / 中华疾病控制杂志
Chinese Journal of Disease Control & Prevention
;
(12)2009.
Article
in Chinese
| WPRIM
| ID: wpr-547602
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
Index:
WPRIM (Western Pacific)
Language:
Chinese
Journal:
Chinese Journal of Disease Control & Prevention
Year:
2009
Type:
Article
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