Comments (6)
Hi! Thank you very much. We are happy about the integration with Darts, we really like your library. We intend to give full maintenance and support to this package and we plan for the APIs to be as stable as possible. Thanks for the croston observation. And thanks for the feedback on documentation.
from statsforecast.
Perfect, thanks!
fyi: here's the PR into Darts to add AutoARIMA (called AutoARIMASF
for the time being) and Croston: unit8co/darts#893.
Is there anything else you'd recommend we should take a look at?
from statsforecast.
Thanks for your work @FedericoGarza. Indeed it was released very recently and I'm very happy to see it in Darts. I'll let you know if I have any feedback (please do the same).
from statsforecast.
Hi @hrzn ! It would be great if the class name was StatsForecastAutoARIMA to match other libraries (sktime for example). Thanks! :)
from statsforecast.
Hi @hrzn ! It would be great if the class name was StatsForecastAutoARIMA to match other libraries (sktime for example). Thanks! :)
Yes sure, I can do that 👍
from statsforecast.
Hi @hrzn. I've seen that StatsForecast is now included in darts. Thank you! Nice work!
Let us know if you have any more questions or feature requests.
from statsforecast.
Related Issues (20)
- Prediction Interval Questions HOT 6
- Croston: Error fitting with 0.0 values HOT 1
- Make best fitted ARIMA an output of AutoARIMA HOT 2
- IMAPA Model not working in statsforecast=="1.7.2" HOT 1
- Allow external regressors TBATS HOT 2
- FutureWarning in AirPassengersDF
- can we reduce the prediction accuracy HOT 18
- [AutoETS] Access the model components (Error, Trend and Seasonality) HOT 1
- MSTL Plot HOT 2
- [AutoTBATS,TBATS] Usage example HOT 3
- AutoARIMA import error HOT 2
- Nixtla statsforecast/statsmodels failing to import polars HOT 3
- Independency of Time Series with Different Unique IDs HOT 2
- [Question] AutoARIMA.forward HOT 5
- Statsforecat.predict expects wrong dataframe shape on X_df HOT 10
- Add a check for fitting a theta model with less than two seasonal periods
- Missing Amazon Forecast results in the experiment docs HOT 4
- AttributeError: 'bool' object has no attribute 'n_windows' when adding confidence level HOT 4
- SeasonalNaive forecasts are not as expected; expected lag 12 but forecast is rounded and slightly off HOT 2
- Getting error when training AutoCES on covid deaths dataset from gluonts HOT 3
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