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Applications of ARIMA model on predictive incidence of influenza

Qi Li

Open publisher page 1 citations

Abstract

Objective To explore the application of auto regressive integrated moving average (ARIMA) and establish a predictive model for influenza to forecast the dynamic trend in order to develop the prevention policy scientifically. Methods Samples which caught influenza from 2002 Jan to 2006 Jun in Chongqing city were subjected. SPSS was used to fit ARIMA model,and Q statistic was used to verify the applicability of the model. Results The model of ARIMA(1,1,1) was established. The statistic of Q was smaller than χ2_α(m), verifying the applicability of this model. Conclusion The ARIMA model can be used to analyze the influenza incidence and make a short-term prediction.

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What this paper is about

Objective To explore the application of auto regressive integrated moving average (ARIMA) and establish a predictive model for influenza to forecast the dynamic trend in order to develop the prevention policy scientifically. Methods Samples which caught influenza from 2002 Jan to 2006 Jun in Chongqing city were subjected. SPSS was used to fit ARIMA model,and Q statistic was used to verify the applicability of the model. Results The model of ARIMA(1,1,1) was established. The statistic of Q was smaller than χ2_α(m), verifying the applicability of this model. Conclusion The ARIMA model can be used to analyze the influenza incidence and make a short-term prediction.

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Available abstract

Objective To explore the application of auto regressive integrated moving average (ARIMA) and establish a predictive model for influenza to forecast the dynamic trend in order to develop the prevention policy scientifically. Methods Samples which caught influenza from 2002 Jan to 2006 Jun in Chongqing city were subjected. SPSS was used to fit ARIMA model,and Q statistic was used to verify the applicability of the model. Results The model of ARIMA(1,1,1) was established. The statistic of Q was smaller than χ2_α(m), verifying the applicability of this model. Conclusion The ARIMA model can be used to analyze the influenza incidence and make a short-term prediction.

Key concepts: Autoregressive integrated moving average, Statistic, Statistics, Term (time), Econometrics, Incidence (geometry), Moving average, Computer science

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