Model detection for grey forecasting model with polynomial term
Published in Communications in Statistics - Simulation and Computation, 2024
This paper studies grey forecasting models with polynomial terms, covering the traditional grey model, the nonhomogeneous grey model, and integer-order grey models with time-power terms as special cases. It proposes a model detection method for identifying which polynomial orders are truly significant, balancing predictive benefit against added model complexity. Simulations and an empirical study on annual health expenditure in China show that the method can recover the true model structure and deliver strong forecasting performance.
Recommended citation: Zhiyuan Ouyang. "Model detection for grey forecasting model with polynomial term." Communications in Statistics - Simulation and Computation, 2024.
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