scikit-hts 0.2.0

Hierarchical Time Series forecasting

Hierarchical Time Series with a familiar API

• Free software: GNU General Public License v3

• 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.

[1]

Forecasting Principles and Practice. Rob J Hyndman and George Athanasopoulos. Monash University, Australia.

Note

STATUS: alpha. Active development, but breaking changes may come.

Features

• Implementation of Bottom-Up, Top-Down, Middle-Out, Forecast Proportions, Average Historic Proportions, Proportions of Historic Averages and OLS revision methods

• 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

Roadmap

• More flexible underlying modeling support

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.