为什么 Python statsmodels...SARIMAX.predict 不起作用？

Question

我正在尝试SARIMAX将 34 个元素的每月时间序列扩展到 35 个元素，假设有 12 个月的季节性成分。

但是，该predict方法因回溯而失败：

<ipython-input-40-151295bf5e3e> in approach_4_stationarity(data_file_name)
     27     sarima = SARIMAX( total_items_array, order = ( 1, 0, 0 ), seasonal_order = (0,0,0,12) )
     28     sarima.fit()
---> 29     next_month_item_cnt = sarima.predict( (1, 0, 0 ), start = 34, end = 34 )
     30     print( "next_month_item_cnt", next_month_item_cnt, file = sys.stderr )
     31     total_items_array = total_items_array.append( next_month_item_cnt )

/opt/conda/lib/python3.6/site-packages/statsmodels/base/model.py in predict(self, params, exog, *args, **kwargs)
    205         This is a placeholder intended to be overwritten by individual models.
    206         """
--> 207         raise NotImplementedError
    208 
    209 

我怎样才能解决这个问题？

Answer 1

该fit方法不会影响模型对象，它返回一个新的结果对象。您可能想要如下所示的内容：

model = SARIMAX(total_items_array, order=(1, 0, 0), seasonal_order=(0,0,0,12))
results = model.fit()
next_month_item_cnt = results.forecast(steps=1)