Comparative study of SARIMA and NARX models in predicting the incidence of schistosomiasis in China

Xinya Yu; Zhuang Chen; Longxing Qi; Xinya Yu; Zhuang Chen; Longxing Qi

doi:10.3934/mbe.2019112

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 4: 2266-2276. doi: 10.3934/mbe.2019112

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Research article Special Issues

Comparative study of SARIMA and NARX models in predicting the incidence of schistosomiasis in China

School of Mathematical Sciences, Anhui University, Hefei, 230601, P.R.China

Received: 15 December 2018 Accepted: 25 February 2019 Published: 15 March 2019

In this paper, based on the data of the incidence of schistosomiasis in China from January 2011 to May 2018 we establish SARIMA model and NARX model. These two models are used to predict the incidence of schistosomiasis in China from June 2018 to September 2018. By comparing the mean square error and the mean absolute error of two sets of predicted values, the results show that the NARX model is better and it has an e ective forecasting precision to incidence of schistosomiasis. Then according to the results, a mixed model called NARX-SARIMA model is used to predict the incidence future trends and make a comparison with the two model. The mixed model has a better application based on its good fitting capability.
- schistosomiasis,
- incidence,
- autoregressive integrated moving average (ARIMA) model,
- NARX model
Citation: Xinya Yu, Zhuang Chen, Longxing Qi. Comparative study of SARIMA and NARX models in predicting the incidence of schistosomiasis in China[J]. Mathematical Biosciences and Engineering, 2019, 16(4): 2266-2276. doi: 10.3934/mbe.2019112

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Abstract

In this paper, based on the data of the incidence of schistosomiasis in China from January 2011 to May 2018 we establish SARIMA model and NARX model. These two models are used to predict the incidence of schistosomiasis in China from June 2018 to September 2018. By comparing the mean square error and the mean absolute error of two sets of predicted values, the results show that the NARX model is better and it has an e ective forecasting precision to incidence of schistosomiasis. Then according to the results, a mixed model called NARX-SARIMA model is used to predict the incidence future trends and make a comparison with the two model. The mixed model has a better application based on its good fitting capability.

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