text: Title: support more than 2 percentiles to be passed for `predict_interval`
  Body: I'm working on creating a back-adapter for `skforecast` models in `sktime`, starting with `ForecasterAutoreg`. The goal is to provide an option to use `skforecast` as an backend alternative to the already existing `make_reduction`. During this, I notice that currently it enforces `interval` to be a list of values in `[0, 100)`, even though it's not necessary that they sum up to 100.
  
  While as a single confidence interval it makes sense, enforcing length does not seem to be a necessity as you are calculating the quantiles from bootstrapping predictions.
  
  https://github.com/JoaquinAmatRodrigo/skforecast/blob/db04f762d878c096b87b97de1a20f35025bbc437/skforecast/ForecasterAutoreg/ForecasterAutoreg.py#L990
  
  If you remove the fixed length requirement, it will be easier to integrate in `sktime` for `predict_quantiles` methods, otherwise it'd need an otherwise unnecessary for loop or calling `predict_bootstrapping` directly and calculating `quantiles` in the back adapter itself. Can it be considered as a feature request?
  
  If you have any other suggestion to address this without this feature request, that will be much appreciated as well.