update changelog

CHANGELOG.md

@@ -11,8 +11,16 @@ but cannot always guarantee backwards compatibility. Changes that may **break co
 
 **Improved**
 
-- 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)
+- 🚀🚀 Introducing Conformal Prediction to Darts: Add calibrated intervals to your model forecasts with the first two conformal prediction models.
+  - `ConformalNaiveModel`: WIP
+  - `ConformalQRModel`: WIP
+- Improvements to `ForecastingModel`:
+  - 🚀🚀 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)
+  - 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).
+- Improvements to Metrics: Added three new quantile interval metrics (plus their aggregated versions):
+  - Interval Winkler Score `iws()`, and Mean Interval Winkler Scores `miws()` (time-aggregated) ([source](https://otexts.com/fpp3/distaccuracy.html))
+  - Interval Coverage `ic()` (binary if observation is within the quantile interval), and Mean Interval Covarage `mic()` (time-aggregated)
+  - Interval Non-Conformity Score for Quantile Regression `incs_qr()`, and Mean ... `mincs_qr()` (time-aggregated) ([source](https://arxiv.org/pdf/1905.03222))
 - 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).