Holt Winter's Time Series Forecasting

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A Python implementation of Holt-Winter's Exponential Smoothing and Forecasting in Python.

Objective

Write a simple to read yet complete implementation of Holt Winter's smoothing/forecasting for use by RIT students. This implementation should support multiple seasons.

This was originally a school project by Eilif Mikkelsen. From time to time, contributions will continue to be made by the original author and other members of the community.

Documentation

Documentation of Github Pages Here

Docs of course can be built by cd docs_gen && make html from a bash shell.

Be sure to commit a rebuild of the docs with a PR!

Installation

1. Download or clone this repository.
2. Point a shell with your target Python environment to this repo's folder on your machine.
3. pip install . or python setup.py install or python3 setup.py install

Examples

A basic usage example can be found in examples/demo.py

Implementation

Currently Implemented (original scope)

• Out of sample prediction
• Multiple seasons
• Additive seasonality

Future Tasks for the Novice

• Multiplicative seasonality

Future Tasks for the Ambitious

• Statsmodels drop-in API compatibility[1]
• Automatic DataFrame index management
• Automatic testing suite

Notes

[1] The inner workings of the statsmodels API were way overkill for this application. The additional complexity would make this package far too complex for a new Python user to modify.