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Nixtla / hierarchicalforecast

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
https://nixtlaverse.nixtla.io/hierarchicalforecast
Apache License 2.0
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forecast_fitted_values() with neuralforecast estimators #179

Closed candalfigomoro closed 7 months ago

candalfigomoro commented 1 year ago

In this example https://nixtla.github.io/hierarchicalforecast/examples/australiandomestictourism.html#computing-base-forecasts

fcst = StatsForecast(df=Y_train_df, 
                     models=[ETS(season_length=4, model='ZZA')], 
                     freq='QS', n_jobs=-1)
Y_hat_df = fcst.forecast(h=8, fitted=True)
Y_fitted_df = fcst.forecast_fitted_values()

you call fcst.forecast_fitted_values(), however the forecast_fitted_values() method seems to be unavailable for neuralforecasts estimators such as NHITS and NBEATSx.

Moreover, it looks like using Y_df is not enough, see https://github.com/Nixtla/hierarchicalforecast/issues/162

How can we get the expected Y_fitted_df data with neuralforecast estimators? Thanks

jmoralez commented 8 months ago

Hey @candalfigomoro. We have an example on how to use neural and mlforecast estimators here. Can we close this issue?

github-actions[bot] commented 7 months ago

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