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目的拟合适合门诊量时间序列资料的预测模型,预测我院2011年门诊量。方法采用ARIMA模型对门诊量进行模型拟合。结果拟合模型参数具有统计学意义,方差估计值为8.97,AIC=1366.888,SBC=1373.676。对模型进行白噪声残差分析,拟合优度统计量表表明最终拟合的ARIMA模型为:(1-B)(1-B12)Yt=-11.7601+(1-0.8527B)(1-0.3947B12)et。结论 ARIMA模型适用于门诊量的时间序列模型拟合,结果显示模型预测值与实际值相符合,在没有外来干预因素影响的情况下,门诊量将会继续上涨。
Objective To fit the prediction model of outpatient time series data to predict the outpatient volume in our hospital in 2011. Methods The ARIMA model was used to fit the outpatient volume. Results The parameters of the fitted model were statistically significant. The estimated variance was 8.97, AIC = 1366.888 and SBC = 1373.676. The white noise residuals of the model were analyzed. The goodness of fit statistics table showed that the final fitted ARIMA model was: (1-B) (1-B12) Yt = -11.7601 + (1-0.8527B) (1-0.3947 B12) et. Conclusions The ARIMA model is suitable for the out-patient time series model fitting. The results show that the model predictive value is in accordance with the actual value, and the outpatient volume will continue to rise without the influence of external factors.