I am trying to implement demand forecast of a produt for a month ahead and then convert it to week wise. I have received 7 years of week wise sales data,did all necesary data preprocessing,train(up to 6 years) &test split(last one year)and then attempted single,double & triple exponential smoothing methods for insample forecast.
When i try to perform out of sample/multi step forecasting(one month ahead),getting following error.
I looked around the web couldn't find sample implementaion in python.Can someone help me on this please.
fit1 = ExponentialSmoothing(np.asarray(tr['sales']) ,seasonal_periods=7 ,trend='mul', seasonal='mul',).fit() df['Hlt_winter'] = fit1.forecast(len(test)+4) ValueError: Length of values does not match length of index