基于配对检验的ARIMA模型在我国甲肝发病数预测中的应用.

Objective: To explore the application of autoregressive integrated moving average (ARIMA) model based on paired test in predicting the incidence of hepatitis A in China, and put forward a new idea and method for evaluating the prediction effect of time series model. Methods: An ARIMA model was established for the monthly incidence of hepatitis A infectious diseases in China from January 2004 to December 2021, and the monthly incidence of hepatitis A infectious diseases from January to August 2022 was predicted. The prediction effect of the model was evaluated by paired t⁃test and error analysis. Results: The results of paired t⁃test showed that there was no significant difference between the monthly incidence of hepatitis A predicted by ARIMA (1, 1, 0) (0, 1, 1)12 model and the actual monthly incidence of hepatitis A (P > 0.05), indicating that the model had good prediction ability, and the mean relative error and standard deviation of the prediction results were 3.86% and 3.25%. Conclusion: ARIMA product season model can accurately predict the incidence trend of hepatitis A in China. The paired test provides an objective basis for evaluating the prediction effect of time series model, and solves the problem of evaluating the prediction effect of time series model well. [ABSTRACT FROM AUTHOR]