I have a time series that I am trying to model with Python's statsmodels ARIMA api. When I apply the following:
from statsmodels.tsa.arima_model import ARIMA model = ARIMA(data['Sales difference'].dropna(), order=(2, 1, 2)) results_AR = model.fit(disp=-1)
I get the following error:
ValueError: The computed initial AR coefficients are not stationary You should induce stationarity, choose a different model order, or you can pass your own start_params.
But I have already differenced the data:
data['Sales'] = data['Sales'] - data['Sales'].shift()
What more can I do to induce stationarity?
And what test is the ARIMA api running to determine that the data is not stationary?