问题描述
我是使用 arima 建模时间序列数据的新手
我有一个使用 Ademic Adar 指数计算的相似度时间序列。但是，当我使用 ARIMA 时，它会不断预测某些数据，我该怎么办？
这就是我所拥有的
Results=np.dstack([aa_matrix,aa_matrix_2,aa_matrix_3,aa_matrix_4,aa_matrix_5,aa_matrix_6])
Results=Results.reshape(-1)
size = int(len(Results) * 0.988597)
train,test = Results[0:size],Results[size:len(Results)]
from statsmodels.tsa.arima.model import ARIMA
model = ARIMA(train,order=(2,1,1))
model_fit = model.fit()
output = model_fit.forecast(steps=len(test))
示例输出
[0.0026541988296397982,0.002654198829639803,0.002654198829639807,0.0026541988296398104,0.0026541988296398134,0.002654198829639816,0.002654198829639818,0.00265419882963982,0.0026541988296398212,0.0026541988296398225,0.0026541988296398234,0.0026541988296398243,0.002654198829639825,0.0026541988296398256,0.002654198829639826,0.0026541988296398264,0.002654198829639827,0.0026541988296398273,0.0026541988296398277,0.0026541988296398277]
我也读过这篇Statsmodels ARIMA: Constant Value for Each Forecast 我也看到一条评论说，尝试添加漂移，但我不知道该怎么做
任何帮助将不胜感激 提前致谢
解决方法
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