Metadata-Version: 2.4
Name: MSFR
Version: 1.1.0
Summary: Python library for multi-seasonal time series regression with Fourier features and smoothing
Author-email: rrayy <taejunham1@gmail.com>, tatatommy6 <tatatommy6@naver.com>
License-Expression: Apache-2.0
Project-URL: Homepage, https://github.com/tatatommy6/multi-seasonal-fourier-regression
Project-URL: Repository, https://github.com/tatatommy6/multi-seasonal-fourier-regression
Project-URL: Issues, https://github.com/tatatommy6/multi-seasonal-fourier-regression/issues
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch==2.8.0
Dynamic: license-file

# multi-seasonal-fourier-regression (MSFR)
This is a python library for multi-seasonal time series regression with Fourier features and smoothing.

## About MSFR

MSFR (Multi-Seasonal Fourier Regression) was created to address the limitations of traditional polynomial regression in modeling periodic data.  
High-order polynomials often lead to overfitting and unstable forecasts, while ignoring the rich seasonal structures present in many real-world time series.  

By incorporating sinusoidal functions as features, MSFR captures both low and high-frequency patterns with fewer parameters,  
providing smoother and more interpretable forecasts for seasonal and multi-seasonal data.
