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.
Predicted Result
PYTHON CODE
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.