What are the advantages of expressing an ARMA model as a state-space-model and do forecasting using a Kalman filter?

This methodology is for example used in the SARIMAX implementation of python-statsmodels:



1 Answer 1


To me one of the main advantages is handling of missing data and uneven time steps. Kalman filter easily handles the missing observations, and actually can be used to impute them.

OLS and MLE don't handle missing data as easily, and not every package will have this feature support unlike Kalman filter.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.