Hierarchical Time Series forecasting
Project description
Hierarchical Time Series with a familiar API
Documentation: https://scikit-hts.readthedocs.io/en/latest/
Overview
Building on the excellent work by Hyndman [1], we developed this package in order to provide a python implementation of general hierarchical time series modeling.
Note
STATUS: alpha. Active development, but breaking changes may come.
Features
Supported and tested on python 3.6, python 3.7 and python 3.8
Implementation of Bottom-Up, Top-Down, Middle-Out, Forecast Proportions, Average Historic Proportions, Proportions of Historic Averages and OLS revision methods
Support for representations of hierarchical and grouped time series
Support for a variety of underlying forecasting models, inlcuding: SARIMAX, ARIMA, Prophet, Holt-Winters
Scikit-learn-like API
Geo events handling functionality for geospatial data, including visualisation capabilities
Static typing for a nice developer experience
Distributed training & Dask integration: perform training and prediction in parallel or in a cluster with Dask
Examples
You can find code usages here: https://github.com/carlomazzaferro/scikit-hts-examples
Roadmap
- More flexible underlying modeling support
[P] AR, ARIMAX, VARMAX, etc
[P] Bring-Your-Own-Model
[P] Different parameters for each of the models
- Decoupling reconciliation methods from forecast fitting
[W] Enable to use the reconciliation methods with pre-fitted models
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
History
0.1.0 (2020-01-02)
First release on PyPI.
0.2.0 (2018-02-13)
Major feature implementation and documentation
Static typing
Testing - 44% coverage
0.2.3 (2020-03-28)
Testing up to 75%
Exogenous variable support
Extensive docs
0.3.0 (2020-03-28)
Parallel and distributed training
0.4.0 (2020-03-28)
Testing for all reconciliation methods, line coverage > 80%
0.4.1 (2020-03-28)
Python 3.6 support
0.5.2 (2020-03-28)
Added support for no revision, thanks @ryanvolpi
Added multiple example at https://github.com/carlomazzaferro/scikit-hts-examples, thanks @vtoliveira
Logging fixes and usability improvements
0.5.3 (2021-02-23)
Support for grouped time series, thanks to @noahsa! See: https://github.com/carlomazzaferro/scikit-hts/pull/51
0.5.4 (2021-04-20)
Fixed long-standing BU forcasting bug, thanks to @javierhuertay! See: https://github.com/carlomazzaferro/scikit-hts/issues/35
Project details
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