Q:

Do we need to stationarize a time series signal when using Kalman filter?

I am working on forecasting the number of logins.
I know that before using ARIMA, it is important to remove trend and seasonality.
But in the case of Kalman filter, I am not sure. After all it is a filter.
Has anyone worked with Kalman filter to make forecasts?
Thanks

A:

From my perspective, the answer is no. In Kalman filter, there's a deterministic system for the hidden variable as well as the observed values. In other words, we don't have any control over whether this system will be stationary or not.

