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Alright I figured it out (maybe) 🙂

horizon = 28
models = [
    SeasonalNaive(season_length=7, prediction_intervals=ConformalIntervals(n_windows=5, h=28)),
    Naive(prediction_intervals=ConformalIntervals(n_windows=5, h=28)),
    HistoricAverage(prediction_intervals=ConformalIntervals(n_windows=5, h=28)),
    CrostonOptimized(prediction_intervals=ConformalIntervals(n_windows=5, h=28)),
    ADIDA(prediction_intervals=ConformalIntervals(n_windows=5, h=28)),
    IMAPA(prediction_intervals=ConformalIntervals(n_windows=5, h=28)),
    AutoETS(season_length=7, prediction_intervals=ConformalIntervals(n_windows=5, h=28))
]

with n_windows however it takes some solid time extra ;D, is there more reading to what hyperparameter makes sense for n_windows ? Thanks.

Hey. You only need to provide prediction_intervals for models that don't support them out of the box, so for example AutoETS should work without it (but you can also compute them using conformal intervals if you want). Does the error only happen for croston? It seems like it's a short serie, can you try reducing n_windows? The n_windows parameter controls how many CV iterations are performed to estimate the errors and build the intervals, you can try 4 for example and it should work well

Thanks for super quick answer.