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.

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.

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

0.5.6 (2021-04-20)

• Fixed input sanitization for convenience methods. See: https://github.com/carlomazzaferro/scikit-hts/issues/65

0.5.7 (2021-05-30)

• Ability to build hierarchies from tabular data. Thanks @noahsa! See: https://github.com/carlomazzaferro/scikit-hts/pull/70

0.5.8 (2021-05-30)

• Fix long-standing bugs related to transformers implementation. See: https://github.com/carlomazzaferro/scikit-hts/issues/66, https://github.com/carlomazzaferro/scikit-hts/issues/33, https://github.com/carlomazzaferro/scikit-hts/issues/38

0.5.9 (2021-05-30)

• Fix long-standing bugs related to handling exogenous variables. See: https://github.com/carlomazzaferro/scikit-hts/issues/55

0.5.10 (2021-06-5)

• Minor bug fix for transforms fixed: https://github.com/carlomazzaferro/scikit-hts/issues/66#issuecomment-855223892

0.5.11 (2021-06-5)

• Further fix to exogenous variable handling, thanks to @wilfreddesert! See: https://github.com/carlomazzaferro/scikit-hts/issues/75