I am using SARIMAX model from the statsmodels library to predict(forecast) future values in a time-series. The library contains four methods: predict(), get_predictions(), forecast(), get forecast(). I understand using the methods prefixed with "get_" allows for multistep predictions. But what is the difference between predicting and forecasting, in this library?
The documentation mentions that forecasting is more suitable for out-of-sample predictions, but would it be wrong to use it for in-sample ones as well? Does the predict function maybe contain some extra handling of over-fitting(which could be a problem when predicting in-sample)?
The results objects also contain two methods that all for both in-sample fitted values and out-of-sample forecasting. They are predict and get_prediction. The predict method only returns point predictions (similar to forecast), while the get_prediction method also returns additional results (similar to get_forecast).
In general, if your interest is out-of-sample forecasting, it is easier to stick to the forecast and get_forecast methods.
Note my question is different to the question about the linguistic meaning of these two words.