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anchor ARIMAS simulation to end of series #1893

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Jul 12, 2023
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3 changes: 2 additions & 1 deletion CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,8 @@ but cannot always guarantee backwards compatibility. Changes that may **break co
- Fixed a bug when loading the weights of a `TorchForecastingModel` trained with encoders or a Likelihood. [#1744](https://github.com/unit8co/darts/pull/1744) by [Antoine Madrona](https://github.com/madtoinou).
- Fixed a bug when using selected `target_components` with `ShapExplainer. [#1803](https://github.com/unit8co/darts/pull/#1803) by [Dennis Bader](https://github.com/dennisbader).
- Fixed `TimeSeries.__getitem__()` for series with a RangeIndex with start != 0 and freq != 1. [#1868](https://github.com/unit8co/darts/pull/#1868) by [Dennis Bader](https://github.com/dennisbader).
- Fixed an issue where `DTWAlignment.plot_alignment` was not plotting the alignment plot of series with a RangeIndex correctly. [#1880](https://github.com/unit8co/darts/pull/1880) by [Ahmet Zamanis](https://github.com/AhmetZamanis) and [Dennis Bader](https://github.com/dennisbader).
- Fixed an issue where `DTWAlignment.plot_alignment()` was not plotting the alignment plot of series with a RangeIndex correctly. [#1880](https://github.com/unit8co/darts/pull/1880) by [Ahmet Zamanis](https://github.com/AhmetZamanis) and [Dennis Bader](https://github.com/dennisbader).
- Fixed an issue when calling `ARIMA.predict()` and `num_samples > 1` (probabilistic forecasting), where the start point of the simulation was not anchored to the end of the target series. [#1893](https://github.com/unit8co/darts/pull/1893) by [Dennis Bader](https://github.com/dennisbader).

**Removed**
- Removed support for Python 3.7 [#1864](https://github.com/unit8co/darts/pull/#1864) by [Dennis Bader](https://github.com/dennisbader).
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1 change: 1 addition & 0 deletions darts/models/forecasting/arima.py
Original file line number Diff line number Diff line change
Expand Up @@ -161,6 +161,7 @@ def _predict(
repetitions=num_samples,
initial_state=self.model.states.predicted[-1, :],
random_state=self._random_state,
anchor="end",
exog=future_covariates.values(copy=False)
if future_covariates
else None,
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