epgm-model 0.1.1

Implementation of the EPGM model for time series forecasting.

EPGM (2,1, Tau)

An open-source Python implementation of the EPGM(2,1,Tau) model from the paper:
A novel dynamic time-delay grey model of energy prices and its application in crude oil price forecasting
https://doi.org/10.1016/j.energy.2022.123968

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Overview

EPGM is a second-order grey forecasting model designed to improve traditional grey models by incorporating a time delay parameter Tau.

This implementation allows fitting and forecasting with the EPGM(2,1,Tau) model, supporting parameter optimization using simulated annealing, regularized regression, and multi-step ahead prediction.

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Features

• Fit EPGM(2,1,Tau) model on univariate time series data
• Optimize model parameters (r1, tau, regularization alpha) via simulated annealing
• Support both unregularized least squares and Ridge regression solvers
• Predict future values with option to constrain predictions to positive values
• Handles data normalization internally
• Built-in evaluation using Mean Absolute Percentage Error (MAPE)
• Plotting utilities for visualizing test set performance

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Installation

pip install epgm_model