From 51b026befec10b3e35dd1d7e879980d43226de3e Mon Sep 17 00:00:00 2001 From: cnhwl Date: Sun, 8 Dec 2024 21:24:25 +0800 Subject: [PATCH] Fix/documentation url of statsforecast models (#2610) * Update sf_auto_arima.py * Update sf_auto_ets.py * Update sf_auto_ces.py * Update sf_auto_theta.py * Update CHANGELOG.md --- CHANGELOG.md | 1 + darts/models/forecasting/sf_auto_arima.py | 2 +- darts/models/forecasting/sf_auto_ces.py | 2 +- darts/models/forecasting/sf_auto_ets.py | 2 +- darts/models/forecasting/sf_auto_theta.py | 2 +- 5 files changed, 5 insertions(+), 4 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index d02bd7258a..2428a90127 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -14,6 +14,7 @@ but cannot always guarantee backwards compatibility. Changes that may **break co - Improvements to `ForecastingModel`: Improved `start` handling for historical forecasts, backtest, residuals, and gridsearch. If `start` is not within the trainable / forecastable points, uses the closest valid start point that is a round multiple of `stride` ahead of start. Raises a ValueError, if no valid start point exists. This guarantees that all historical forecasts are `n * stride` points away from start, and will simplify many downstream tasks. [#2560](https://github.com/unit8co/darts/issues/2560) by [Dennis Bader](https://github.com/dennisbader). - Added `data_transformers` argument to `historical_forecasts`, `backtest`, `residuals`, and `gridsearch` that allow to automatically apply `DataTransformer` and/or `Pipeline` to the input series without data-leakage (fit on historic window of input series, transform the input series, and inverse transform the forecasts). [#2529](https://github.com/unit8co/darts/pull/2529) by [Antoine Madrona](https://github.com/madtoinou) and [Jan Fidor](https://github.com/JanFidor) - Added `series_idx` argument to `DataTransformer` that allows users to use only a subset of the transformers when `global_fit=False` and severals series are used. [#2529](https://github.com/unit8co/darts/pull/2529) by [Antoine Madrona](https://github.com/madtoinou) +- Updated the Documentation URL of `Statsforecast` models. [#2610](https://github.com/unit8co/darts/pull/2610) by [He Weilin](https://github.com/cnhwl). **Fixed** diff --git a/darts/models/forecasting/sf_auto_arima.py b/darts/models/forecasting/sf_auto_arima.py index cd8569aede..dba6e1c6bc 100644 --- a/darts/models/forecasting/sf_auto_arima.py +++ b/darts/models/forecasting/sf_auto_arima.py @@ -32,7 +32,7 @@ def __init__( It is probabilistic, whereas :class:`AutoARIMA` is not. We refer to the `statsforecast AutoARIMA documentation - `_ + `_ for the exhaustive documentation of the arguments. Parameters diff --git a/darts/models/forecasting/sf_auto_ces.py b/darts/models/forecasting/sf_auto_ces.py index 5ec8fc1a44..8f3a9f8adb 100644 --- a/darts/models/forecasting/sf_auto_ces.py +++ b/darts/models/forecasting/sf_auto_ces.py @@ -18,7 +18,7 @@ def __init__(self, *autoces_args, **autoces_kwargs): We refer to the `statsforecast AutoCES documentation - `_ + `_ for the exhaustive documentation of the arguments. Parameters diff --git a/darts/models/forecasting/sf_auto_ets.py b/darts/models/forecasting/sf_auto_ets.py index 95572c42fe..d4959db607 100644 --- a/darts/models/forecasting/sf_auto_ets.py +++ b/darts/models/forecasting/sf_auto_ets.py @@ -31,7 +31,7 @@ def __init__( on Numba and jit compilation. We refer to the `statsforecast AutoETS documentation - `_ + `_ for the exhaustive documentation of the arguments. In addition to the StatsForecast implementation, this model can handle future covariates. It does so by first diff --git a/darts/models/forecasting/sf_auto_theta.py b/darts/models/forecasting/sf_auto_theta.py index 626c570665..628c1a1f04 100644 --- a/darts/models/forecasting/sf_auto_theta.py +++ b/darts/models/forecasting/sf_auto_theta.py @@ -26,7 +26,7 @@ def __init__(self, *autotheta_args, **autotheta_kwargs): It is probabilistic, whereas :class:`FourTheta` is not. We refer to the `statsforecast AutoTheta documentation - `_ + `_ for the exhaustive documentation of the arguments. Parameters