197-31: Biosurveillance and Outbreak Detection Using the ARIMA and LOGISTIC Procedures
نویسندگان
چکیده
The main objective of this paper is to show potential usefulness of the combination of autoregressive integrated moving average (ARIMA) models and logistic regression with automatic model selection (see our work presented at SUGI’28 and SUGI’29.) Timeseries analysis with ARIMA provides only one perspective of the information in the surveillance data (i.e. the number of patients as a function of time). The information about the geographical location of the patients provides a second perspective. We would like to combine both perspectives.
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