I'm trying to get time series prediction using the following code.
from statsmodels.tsa.holtwinters import ExponentialSmoothing as HWES
#read the data file. the date column is expected to be in the mm-dd-yyyy format.
df_train_y = pd.DataFrame(data = tsne_train_output)
df_train_y.index.freq = 'd'
df_test_y = pd.DataFrame(data = tsne_test_output)
df_test_y.index.freq = 'd'
#plot the data
df_train_y.plot()
plt.show()
#build and train the model on the training data
model = HWES(df_train_y, seasonal_periods=144, trend='add', seasonal='add')
fitted = model.fit(optimized=True, use_brute=True)
#print out the training summary
print(fitted.summary())
#create an out of sample forcast for the next 12 steps beyond the final data point in the training data set
trend_forecast = fitted.forecast(steps= 157200)
And my data looks like this:
df_train_y >>
y_train
0 0
1 0
2 0
3 0
4 0
... ...
366755 65
366756 66
366757 63
366758 65
366759 68
When I'm executing the above code on my data, I'm getting the following error:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-137-66fe58a542ec> in <module>()
23
24 #create an out of sample forcast for the next 12 steps beyond the final data point in the training data set
---> 25 trend_forecast = fitted.forecast(steps= '157200')
1 frames
/usr/local/lib/python3.7/dist-packages/statsmodels/tsa/holtwinters.py in forecast(self, steps)
344 try:
345 freq = getattr(self.model._index, 'freq', 1)
--> 346 start = self.model._index[-1] + freq
347 end = self.model._index[-1] + steps * freq
348 return self.model.predict(self.params, start=start, end=end)
TypeError: unsupported operand type(s) for +: 'int' and 'str'
So I tried to check the type of operands in the line 346,
upon running type(fitted.model._index[-1]) I'm getting int; also I edited the code in holtwinters.py by typecasting all operands to int using int() but still the error persists.
I have reported this issue in the github repo for statsmodels here. And asked same question in datascience stackexchange, but got nothing. DS Stackexchange question link