I am trying to develop a time series model using autoregression. The data set is like as follows
INDEX MAXIMA 0 0.743 1 0.837 2 0.838 4 0.896 5 1.014 6 1.003 7 1.01 8 1.101 9 1.097
The Maxima point is given is the largest points on each curve. Basically, I have to perform multi-step forecasting (at least 9 steps ahead). I've done it using the
recursive approach. but the accuracy of the prediction getting worse as it reaches the end.
Using the AR model from stats model
# fit model for MAX VALUE model = AR(data) model_fit = model.fit() yhat_max = model_fit.predict(len(data),len(data]))
For obtaining an accurate prediction, What changes should be done in the approach? or Do I have to change the model?
Any kind of help is appreciated.