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Releases: Nixtla/statsforecast

v1.6.0

13 Nov 18:17
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Republish of the 1.6.0 release from August 23rd 2023, since it disappeared from github.

New Features

  • Conformal Prediction @kvnkho (#592)
  • Adding levels to distributed backends @kvnkho (#581)
  • [FEAT] Add ConstantModel and ZeroModel @FedericoGarza (#568)
  • [FEAT] Add NaNModel @FedericoGarza (#567)
  • [FEAT] Add conformal intervals Theta family @FedericoGarza (#501)
  • [FEAT] Add conformal intervals for CES @FedericoGarza (#500)
  • [FEATURE] Polars support @akmalsoliev (#448)
  • [FEAT] Add conformal intervals to arima family @FedericoGarza (#488)
  • [FEAT] Add conformal intervals to StatsForecast class @FedericoGarza (#487)
  • [FEAT] Add conformal prediction for AutoARIMA @FedericoGarza (#486)
  • [FEAT] Return plot object @FedericoGarza (#465)
  • [FEAT] Add stl_kwargs to MSTL @FedericoGarza (#462)
  • [FEAT] Support pandas 2.0 changes @FedericoGarza (#456)

Breaking Change

Bug Fixes

  • take shallow copy on dataframe processing and fix get_cmap deprecation @jmoralez (#617)
  • fix arima max order params @jmoralez (#613)
  • Fix iteration range in non-stepwise AutoARIMA @manuel-calzolari (#601)
  • [Core] Fixed RuntimeWarning Generated by _get_cols (#538) @taniishkaaa (#563)
  • [FIX] Unnecessary datetime column conversion @akmalsoliev (#558)
  • [FIX] Accommodated switch to jupyter-lab @akmalsoliev (#511)
  • [FIX] Polars hotfix @akmalsoliev (#503)
  • [FIX] Added polars to settings.ini @akmalsoliev (#499)
  • [FIX] HoltWinters forecasts (weekly seasonality) @FedericoGarza (#483)
  • [FIX] Consider correct seasonality for exp smoothing @FedericoGarza (#474)
  • Remove unused levels from categorical unique_id @nickto (#473)
  • [FIX] Add protection ETS zero division error @FedericoGarza (#470)
  • [FIX] allow period=1 using mstl @FedericoGarza (#463)
  • [FIX] ets forbidden component combinations @FedericoGarza (#461)
  • [FIX] Different results between forecast and fit/predict MSTL @FedericoGarza (#446)
  • Stop using mutable defaults for ets_f lower and upper arguments @kschmaus (#437)
  • [FIX] Distributed behaviour with exogenous variables @FedericoGarza (#427)

Documentation

  • Adding details to Conformal Prediction docs @kvnkho (#607)
  • Tutorial for Conformal Prediction @kvnkho (#597)
  • [FIX] SeasonalNaive docs @nelsoncardenas (#588)
  • Fix incorrect parameter name in How-To-Guides @yibenhuang (#584)
  • Changing Load Forecasting Data Souce @kvnkho (#572)
  • [DOCS] Adding GARCH and ARCH to index @kvnkho (#571)
  • Fix broken doc links @andrewgross (#566)
  • Fixing broken links @kvnkho (#559)
  • Updated the document to reflect the deprecation of ETS in favor of AutoETS (#319) @taniishkaaa (#561)
  • [DOC] renamed files for order @mergenthaler (#554)
  • Update nbs/ @FedericoGarza (#548)
  • [FIX] Restructure how-to guides @FedericoGarza (#547)
  • [DOCS] AutomaticForecasting @mergenthaler (#545)
  • Updating Distributed Documentation @kvnkho (#541)
  • Update nbs/ @FedericoGarza (#546)
  • [FEAT] New docs structure @FedericoGarza (#534)
  • [DOCS] Polars documentation @akmalsoliev (#527)
  • Update nbs/docs/contribute/ file @FedericoGarza (#544)
  • Update nbs/docs/contribute/ file @FedericoGarza (#543)
  • Update nbs/ file @FedericoGarza (#542)
  • Update CONTRIBUTING.md file @FedericoGarza (#533)
  • [FEAT] Add mlforecast to ensemble example @FedericoGarza (#502)
  • [FIX] Link end to end pipeline @FedericoGarza (#477)
  • Update README.md @mergenthaler (#468)
  • [DOCS] Added more instructions on nbdev @akmalsoliev (#449)
  • [DOCS] Hide utils fns from core @FedericoGarza (#429)
  • Fix naive model description @shagn (#268)

Enhancement

  • check for level when prediction_intervals are set @jmoralez (#615)
  • raise informative error when series are too short for cross_validation @jmoralez (#610)
  • Add release drafter @FedericoGarza (#514)
  • Add issue template files @FedericoGarza (#513)
  • Add issue template @FedericoGarza (#512)

v1.5.0

28 Feb 19:25
dc900bd
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What's Changed

Features

New models

  • [FEAT] ARIMA model (no auto version) in #383
  • [FEAT] AutoRegressive model in #387
  • [FEAT] GARCH and ARCH models in #403

New functionality

Forward methods

Now you can pre-train a model and use new data to make forecasts through the forward method. Supported models:

  • [FEAT] Add forward method to Theta models in #362
  • [FEAT] Add forward method to ETS models in #363
  • [FEAT] Add forward method to AutoCES class in #364
  • [FEAT] Add forward method to MSTL model in #369
  • [FEAT] Add forward method to AutoARIMA (ARIMA and AutoRegressive) in #368
Misc
  • [FEAT] Add alias argument to models (fit the same instance of models with different names) in #357
  • [FEAT] Add cross-validation without refit (using the forward method) in #370
  • [FEAT] Allow seasonality greater than 24 for ETS in #384
  • [FEAT] Allow passing fixed coefficients for Arima in #386
  • [FEAT] AutoCES prediction intervals in #394 (now StatsForecast is fully probabilistic)
  • [FEAT] Add cla workflow in #351
  • [FEAT] Add pypi downloads badge in #352
  • [FEAT] Ignore jupyter notebooks as part of languages in #356
  • [FEAT] Add nbdev merge to git attributes in #365
  • [FEAT] Add citation in #366
  • [FEAT] Update table of models in #396

Experiments

  • [FEAT] Add M5 and M4-Daily experiments (Amazon Forecast) in #332
  • [FEAT] Test recover M3 performance in #385
  • [FEAT] BigQuery comparison in #421
  • [FEAT] Experiments for ETS prediction intervals for multiple confidence levels in #377
  • [FEAT] Add M3 experiment in #348
  • [FEAT] Add a test ensuring the m3 performance is recovered in less than two minutes in #388

Tutorials

  • [FEAT] Improved intermittent data nb in #359
  • [FEAT] Add statistical and neural methods tutorial in #399
  • [FEAT] Improve anomaly detection nb in #338
  • [FEAT] GARCH and ARCH models tutorial in #418
  • [FEAT] Improved notebook on prediction intervals in #358
  • [FEAT] Improved notebook on exogenous regressors in #392
  • [FEAT] Improve documentation in #376

Fixes

  • [FIX] Exponential Smoothing description in #346
  • [FIX] Changed dataset and model to make example easier to follow in #345
  • [FIX] Readme M3 typo in #350
  • [FIX] Delete CLA.yml in #355
  • [FIX] Broken link in #360
  • [FIX] Clean aws nbs in #361
  • [FIX] Add correct link to hierarchicalforecast by #372
  • [FIX] Recover table-based documentation (core nb, compatible with docstrings) in #374
  • [FIX] update sklearn -> scikit-learn in #375
  • [FIX] Ray CI in #381
  • [FIX] Links and typos in documentation in #390
  • [FIX] Correct evaluation using Winkler score by @MMenchero in #395
  • [FIX] Recover plots prediction intervals tutorial in #398
  • [FIX] Use https links instead of s3 uris (stat-neural tutorial) in #400
  • [FIX] New nbdev clean behaviour in #412
  • [FIX] Model imports in #408

New dependencies

  • [FEAT] plotly-resampler as plotting engine in #354
  • [FEAT] Move Fugue to core dependency in #419

New Contributors

Full Changelog: v1.4.0...v1.5.0

v1.4.0

01 Dec 04:09
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What's Changed

  • feat: Added prediction intervals for insample and ETS models in #328
  • [FEAT] Add plot anomalies option in #341
  • [DOCS] Improve README and docs page index in #344

Full Changelog: v1.3.2...v1.4.0

v1.3.2

28 Nov 17:50
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What's Changed

  • [FIX] Improvements to StatsForecast's plot method in #312
  • [FEAT] Add plotly as engine to StatsForecast's plot method in #313
  • [FEAT] Add autowidth to plotly engine in #314
  • feat: add new documentation in #317
  • [FIX] ETS for inttermitent series in #315
  • [FIX] Theta for intermittent series in #316
  • [FEAT] Rename ETS to AutoETS in #318
  • [FEAT] Change library to newest black formatting in #320
  • [FIX] Add new plot method to mstl example in #324
  • [FIX] Build docs for Theta model in #322
  • [FIX] Isolate elements for all subplots plotly in #323
  • Fix/multiple seas docs in #325
  • [FEAT] Add mstl experiment in #326
  • [FIX] Prevent futurewarning series indexing in #327
  • Fix sidebar in #331
  • feat: Improved tutorial on Cross-Validation in #333
  • Feat/improve prediction intervals in #336
  • fix: Improved AutoARIMA plot in #334
  • docs: ERCOT electricity demand peak forecasting in #335
  • docs: fix peak demand plot in #339

New Contributors

Full Changelog: v1.3.1...v1.3.2

v1.3.1

17 Nov 18:03
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What's Changed

  • [FEAT] Add plot method to StatsForecast class in #305
  • [FEAT] New Issues Templates in #307
  • [FIX] make logging config local to package in #275
  • [FIX] Error when ds column is object in #309

New Contributors

Full Changelog: v1.3.0...v1.3.1

v1.3.0

15 Nov 00:59
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What's Changed

  • [FIX] Use conda env for ray tests in #297
  • [FIX] Source code broken links in #293
  • [FIX] Sparse models with zero-valued time series in #294
  • [FIX] Add explicit optional argument (PEP-484) in #301
  • [FIX] SeasonalNaive in #302
  • [FEAT] Add exogenous variables to fugue's backend in #300
  • [FEAT] Add Theta methods in #299
  • [FEAT] Add MSTL example and comparison in #295
  • [FEAT] Add backend argument to StatsForecast class in #303

Full Changelog: v1.2.1...v1.3.0

v1.2.1

02 Nov 17:42
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What's Changed

  • [FEAT]: Add fallback model to cross validation in #289

Full Changelog: v1.2.0...v1.2.1

v1.2.0

31 Oct 17:46
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What's Changed

  • [FEAT] MSTL model n #284

Full Changelog: v1.1.3...v1.2.0

v1.1.3

25 Oct 21:01
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What's Changed

  • [FEAT] Add progress bar for sequential tasks in #280

Full Changelog: v1.1.2...v1.1.3

v1.1.2

24 Oct 17:30
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What's Changed

  • [FEAT] Improve navbar docs in #262
  • [FEAT] Add ETS to spark results in #264
  • [FEAT] Improve CES results in #265
  • [FEAT] Add fallback model to distributed backends in #277
  • [FIX] Backend docs in #278

Full Changelog: v1.1.1...v1.1.2