[ENH] Using contemporaneous values of exogenous variables in forecasting reduction

[mloning]

Is your feature request related to a problem? Please describe.
Currently, we only use lagged values of exogenous variables in forecasting reductions, up to the cutoff point, like the endogenous series. However, it is common to use values of the exogenous variables up to the step of the forecasting horizon to be predicted (contemporaneous values).

Describe the solution you'd like

• Add option via keyword argument to reduction approaches to include contemporaneous values
• Implement handling of contemporaneous values

[KishManani]

Hi @mloning! I think it would be great to add the option to have exogenous features, which are known both during the forecast horizon and during the training period, for forecasting with standard ML models that operate on tabular data.

I would like to work on this feature. I understand this is quite an old issue. Is there any additional context or factors I should take into account? Thank you!

[fkiraly]

@KishManani, I think this is still not implemented in the reduction classes, where it should be possible to specify lags of zero.

@danbartl was recently working close to these classes, but not on the "zero lags" issue itself, as far as I know.

What's the newest on this, @danbartl? What would be the best, compartmentalized way to get this feature in?

[fkiraly]

@KishManani, I've looked into the reducer and tried to "upgrade" it, but ended up rewriting it using the Lag transformer class. Have a look at this prototype: #2833

Might be worth working on this together?