YU Yan , HOU Xin-yi , SU Hui-jia , REN Hong . Application of Seasonal Autoregressive Integrated Moving Average Model to Road Traffic Injury Prediction in Shanghai[J]. Journal of Environmental and Occupational Medicine, 2012, 29(9): 539-542.
Citation: YU Yan , HOU Xin-yi , SU Hui-jia , REN Hong . Application of Seasonal Autoregressive Integrated Moving Average Model to Road Traffic Injury Prediction in Shanghai[J]. Journal of Environmental and Occupational Medicine, 2012, 29(9): 539-542.

Application of Seasonal Autoregressive Integrated Moving Average Model to Road Traffic Injury Prediction in Shanghai

  • Objective To explore the feasibility of seasonal autoregressive integrated moving average (SARIMA) model in predicting road traffic injury,and to provide reference for road traffic injury trends in Shanghai.

    Methods A SARIMA model was presented to fit the seasonal road traffic mortality data of Shanghai (2000-2009) via EVIEWS software,and estimated mortalities of 2010 were verified with the actual data.

    Results The seasonal component was statistically significant in Shanghai's road traffic mortality data.A decreasing trend was observed in the trend component of the model.SARIMA (2,1,0)(0,1,1)4 was the best fitting model among various candidate models.The predicted seasonal mortalities of 2010 were 1.49/105,1.74/105,1.93/105,and 2.06/105 respectively.The actual values were all in the prediction intervals,and the residuals were considered as white noise serial.The verification with actual data passed our test.

    Conclusion A SARIMA model can be used in accurate trends prediction of road traffic injury and therefore can provide evidences for road traffic injury intervention.

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