Regarding my initial question (
https://nixtlacommunity.slack.com/archives/C031EJJMH46/p1693989589210909) I would like to ask if my approach is the recommended way to do an extensive cross_validation in the special case that the forecasting horizon is only 1? I am asking because all examples in the documentation show the usage of 3<n_windows<20 which essentially means only "20 crossvalidated days " in the case of h=1.
Also, I would like to ask if the Auto* Models perform hyperparameter tuning and model selection for each window inside the cross validation? Or, do they only perform one initial model selection on the whole time series, find the best model, and use that best model for each window inside the cross validation?
Thank you in advance!