0.16.0

New features and enhancements

• PatchTST: Add support for dynamic features by @rshyamsundar in #3167

Fixes

• Fix freq string issues in datasets by @lostella in #3232

Documentation

• Add model card from PR 2748 by @robert501128 in #3180

Dependencies updates

• Bump pytorch lightning compat by @lostella in #3195
• Update: Import of gluonts modules in pts module by @ClaraGrthns in #3194
• Bump torch from 1.13.1 to 2.2.0 in /src/gluonts/nursery/daf by @dependabot in #3204
• Upgrade dependencies in nursery by @lostella in #3206
• Bump dependency version ranges for numpy & lightning by @shchur in #3226
• Ignore cpflows dependencies in test workflows, fix numpy 2 incompatibilities. by @lostella in #3227
• Update gluonts.shell requirements by @lostella in #3233

Testing

• Drop Python 3.8 from workflows, run on 3.11 by @lostella in #3228

New Contributors

• @robert501128 made their first contribution in #3180
• @ClaraGrthns made their first contribution in #3194

Full Changelog: v0.15.1...v0.16.0

0.16.0rc1

<!-- 
## What's Changed
* Docs: fix custom pytorch model tutorial by @lostella in https://github.com/awslabs/gluonts/pull/3188
* Bump pytorch lightning compat by @lostella in https://github.com/awslabs/gluonts/pull/3195
* Update: Import of gluonts modules in pts module by @ClaraGrthns in https://github.com/awslabs/gluonts/pull/3194
* Bump torch from 1.13.1 to 2.2.0 in /src/gluonts/nursery/daf by @dependabot in https://github.com/awslabs/gluonts/pull/3204
* Upgrade dependencies in nursery by @lostella in https://github.com/awslabs/gluonts/pull/3206
* Bump dependency version ranges for numpy & lightning by @shchur in https://github.com/awslabs/gluonts/pull/3226
* Ignore cpflows dependencies in test workflows, fix numpy 2 incompatibilities. by @lostella in https://github.com/awslabs/gluonts/pull/3227

**Full Changelog**: https://github.com/awslabs/gluonts/compare/v0.15.1...v0.16.0rc1 
-->

0.15.1

Backporting fixes:

• Fix incorrect input routing for models #3186 (by @shchur)
• Docs: fix custom pytorch model tutorial #3188 (by @lostella)
• Enable QuantileOutput for TiDE model #3189 (by @shchur)

0.15.0

New features

• add iTransformer multivariate forecaster (#3017) by @kashif
• Add TiDE model (#3096) by @maxc01
• Add ercot dataset (#3148) by @lostella
• Add ETT datasets (#3149) by @lostella
• Add item_id to ERCOT and ETT datasets (#3150) by @shchur
• Add Seasonal Aggregate Predictor (#3162) by @rshyamsundar

Model updates

• Add option to provide function for season_length in SeasonalNaivePredictor (#3033) by @lostella
• R: add ARIwith exogenous regressors (#3086) by @leica2023

Breaking changes

• ev: Batch data for faster evaluation. (#3051) by @lostella
• Unify QuantileOutput and DistributionOutput (#3093) by @shchur
• Rotbaum: turn to json-based serialization (#3176) by @lostella

Fixes

• Fix issues related to new Pandas offset names (#3117) by @lostella
• Fix loader for the M5 dataset (#3151) by @shchur
• Fix loaders for M5 & ETT datasets (#3155) by @shchur
• Fix item_id for M5 dataset (#3156) by @shchur
• Serde: limit decode code execution (#3175) by @lostella

Dependencies

• Nursery: bump up pyarrow requirement in gluonts.nursery.tsbench (#3056) by @lostella
• Bump scikit-learn from 0.23.2 to 1.0.1 in /src/gluonts/nursery/daf (#3118) by @dependabot
• Bump sklearn version in nursery subpackages (#3120) by @lostella
• Bump dependencies versions to address dependabot alerts (#3173) by @lostella
• Bump dependencies versions to address dependabot alerts, again (#3174) by @lostella

Other changes

• update dockerfile python version to 3.8 (#3072) by @melopeo
• Update REFERENCES.md (#3078) by @abdulfatir
• CI: run R tests on push (#3089) by @lostella
• CI: chain requirements to ensure compatibility (#3112) by @Borda
• test: unify using @pytest.mark.flaky(...) & bump pytest plugins (#3132) by @Borda
• Add Chronos Breaking News (#3154) by @abdulfatir
• lint: freeze & run Black version 24.02 (#3131) by @Borda
• ci: update lints Ruff & docformatter (#3130) by @Borda
• Extend test coverage for pandas frequencies (#3179) by @shchur
• Tests: xfail test for fourier.arima.xreg (#3182) by @lostella

0.14.4

Backporting fixes:

• Fix type annotation for device in PyTorchPredictor #3094 by @lostella
• extend exception for invalid offset_name #3115 by @Borda

0.14.3

Backporting:

• Fix Rotbaum serialization and deserialization #3068 by @pantanurag555
• Fix Rotbaum to handle short series #3073 by @leica2023

0.13.9

Backporting:

• Fix Rotbaum serialization and deserialization #3068 by @pantanurag555
• Fix Rotbaum to handle short series #3073 by @leica2023

0.14.2

Backporting fixes:

• Fix iterable.Cached. #3060 by @jaheba
• Torch: Remove double caching of dataset. #3061 by @jaheba

0.14.1

Backporting fixes:

• Fix edge cases in metric computation #3037 (@lostella)
• Refactor tests for ev.aggregations #3038 (@lostella)
• Add plt.show() to README #3043 (@lostella)
• Rotbaum: Add item-id to forecast. #3049 (@jaheba)
• Fix mypy checks #3052 (@lostella)

0.13.8

Backporting fixes:

• Fix edge cases in metric computation #3037 (@lostella)
• Refactor tests for ev.aggregations #3038 (@lostella)
• Rotbaum: Add item-id to forecast. #3049 (@jaheba)
• Fix mypy checks #3052 (@lostella)