Question

我已经编写了以下代码来使用统计模型的ARIMA来预测数据，但是我的结果与实际数据不匹配，并且在最初几次预测在图上给出一条直线水平线后，预测值几乎不变。

如果预测是针对第二个差分顺序，因为我使用了d = 2，我如何得到同一模型的原始数据的预测。

arima_mod = sm.tsa.ARIMA(df, (1,2,0)).fit()
print(arima_mod.params)
print(arima_mod.summary())
predict_workshop = arima_mod.predict('2011-04-01', '2011-05-30',dynamic=True)
print(predict_workshop)

实际数据

2011-04-01      356.839  
2011-04-02      363.524  
2011-04-03      332.864  
2011-04-04      336.228  
2011-04-05      264.749  
2011-04-06      321.212  
2011-04-07      384.382  
2011-04-08      273.250  
2011-04-09      307.062  
2011-04-10      326.247  
2011-04-11      222.521  
2011-04-12      135.326  
2011-04-13      374.953  
2011-04-14      329.583  
2011-04-15      358.853  
2011-04-16      343.169  
2011-04-17      312.086  
2011-04-18      339.302  
2011-04-19      300.534  
2011-04-20      367.166  
2011-04-21      178.670  
2011-04-22      320.823  
2011-04-23      349.995  
2011-04-24      323.120  
2011-04-25      331.665  
2011-04-26      352.993  
2011-04-27      359.253  
2011-04-28      308.281  
2011-04-29      329.357  
2011-04-30      301.873

预测值

2011-04-01   -50.693560  
2011-04-02    30.715553  
2011-04-03   -19.081318  
2011-04-04    11.378766  
2011-04-05    -7.253263  
2011-04-06     4.143701  
2011-04-07    -2.827670  
2011-04-08     1.436625  
2011-04-09    -1.171787  
2011-04-10     0.423744  
2011-04-11    -0.552221  
2011-04-12     0.044764  
2011-04-13    -0.320404  
2011-04-14    -0.097036  
2011-04-15    -0.233667  
2011-04-16    -0.150092  
2011-04-17    -0.201214  
2011-04-18    -0.169943  
2011-04-19    -0.189071  
2011-04-20    -0.177371  
2011-04-21    -0.184528  
2011-04-22    -0.180150  
2011-04-23    -0.182828  
2011-04-24    -0.181190  
2011-04-25    -0.182192  
2011-04-26    -0.181579  
2011-04-27    -0.181954  
2011-04-28    -0.181724  
2011-04-29    -0.181865  
2011-04-30    -0.181779

Answer 1

一点点暗示。您应该在11,12,21期间包含一个虚拟干预变量。此模型不需要加倍差异。只需一个拦截和3个干预变量就可以了。 Y（T）= 332.20
+ [X1（T）] [（ - 196.87）]：PULSE 12 + [X2（T）] [（ - 153.53）]：PULSE 21 + [X3（T）] [（ - 109.68）]：PULSE 11 + + [A（T）]

Statsmodel ARIMA预测不匹配

1 个答案: