7. When no viable models can be found¶
For certain time series, the search may return no viable models:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
"Could not successfully fit a viable ARIMA model "
ValueError: Could not successfully fit a viable ARIMA model to input data.
See http://alkaline-ml.com/pmdarima/no-successful-model.html for more information on why this can happen.
This can happen for a number of reasons:
- Most commonly, the roots of your model may be nearly non-invertible, meaning the inverted roots
lie too close to the unit circle. Here’s a good blog post
on the subject. Make sure
traceis truthy in order to see these warnings when fitting your model.
- Sometimes, your data may not be stationary and can raise errors from statsmodels when fitting. In this case,
the stepwise algorithm will filter out problem model fits. This can arise in a number of situations, ranging
from non-stationarity to actual code errors. Setting
error_action='trace'will log the stacktraces of any errors encountered during the search.
- Your input data may not be suitable for ARIMA modeling. For instance, it could be a simple polynomial or solved by linear regression (i.e., differencing the time series has made it perfectly constant).
Make sure to set
trace to at least 1 in order to see the search progress, and to a value >1 to see the
maximum trace logging available. If you still cannot diagnose why you are getting this error message, consider
Filing a bug.