ARIMA模型每周时间序列d的预测误差

Question

我用ARIMA模型来预测产品的销售量。数据保存在csv文件中，时间间隔为1周，从2015年1月1日到2016年11月24日。我试图预测未来9个步骤，即未来9个星期。在

csv中的数据：

"01-01-2015",9
"08-01-2015",8
"15-01-2015",13
"22-01-2015",10
"29-01-2015",12
"05-02-2015",5
"12-02-2015",4
"19-02-2015",6
"26-02-2015",9
"05-03-2015",3
"12-03-2015",3
"19-03-2015",2
...

这是我使用的代码：

^{pr2}$

这个模型适用于每月的数据[对于其他csv文件]，但是对于这个每周的数据会给出错误。错误如下：

Traceback (most recent call last):
File "H:\p36564\fit_net1.py", line 57, in <module>
pred_uc.predicted_mean.plot(ax=ax, label='Forecast')
File "H:\p36564\lib\site-packages\pandas\plotting\_core.py", line 2503, in __call__
**kwds)
File "H:\p36564\lib\site-packages\pandas\plotting\_core.py", line 1927, in plot_series
**kwds)
File "H:\p36564\lib\site-packages\pandas\plotting\_core.py", line 1729, in _plot
plot_obj.generate()
File "H:\p36564\lib\site-packages\pandas\plotting\_core.py", line 258, in generate
self._post_plot_logic_common(ax, self.data)
File "H:\p36564\lib\site-packages\pandas\plotting\_core.py", line 396, in _post_plot_logic_common
fontsize=self.fontsize)
File "H:\p36564\lib\site-packages\pandas\plotting\_core.py", line 470, in _apply_axis_properties
labels = axis.get_majorticklabels() + axis.get_minorticklabels()
File "H:\p36564\lib\site-packages\matplotlib\axis.py", line 1245, in get_majorticklabels
ticks = self.get_major_ticks()
File "H:\p36564\lib\site-packages\matplotlib\axis.py", line 1396, in get_major_ticks
numticks = len(self.get_major_locator()())
File "H:\p36564\lib\site-packages\matplotlib\dates.py", line 1249, in __call__
self.refresh()
File "H:\p36564\lib\site-packages\matplotlib\dates.py", line 1269, in refresh
dmin, dmax = self.viewlim_to_dt()
File "H:\p36564\lib\site-packages\matplotlib\dates.py", line 1026, in viewlim_to_dt
.format(vmin))
ValueError: view limit minimum -36710.65 is less than 1 and is an invalid Matplotlib date value. This often happens if you pass a non-datetime value to an axis that has datetime units.

可能出什么问题了？在