The sequential regression analysis was adopted to screen off the secondary factors, and the Kalman filtering technique was used to estimate innovation coefficients of the model dynamically.
通过逐步回归分析方法剔除次要影响因素，并采用卡尔曼滤波方法动态预测回归残差项。
The forecast model includes three parts of the sequential auto-regression item, linear regression item and double-linear item.
预测模型包含时序自回归项、线性回归项和双线性项三部分。
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