I'm trying to fit an ARMA(1,0) model for a timeseries that start at $10$ and drops slowly to $4$ in around $180$ steps. For this, I've tried to fit an ARMA model in python using the following:
# contrived dataset data1 = data['beta_0'].tolist() # fit model model = ARMA(data1, order = (1,0)) model_fit = model.fit()
The results are as follows:
I'm having trouble understanding why the constant would be so big. Wouldn't this mean that if you say for instance that $y_0 = 10$ (as it is in my time series), then $y_1 = 6.8840 + 0.9916y_0 + \epsilon$. I would assume that then the values of this time series would blow up right?
Then how can it be that this is the output for a series that drops slowly from 10 to 4?
Any help would be much appreciated.