Regression modelEconometrics / time series

Fourier SARIMA Model

The Fourier SARIMA model extends the classical Seasonal ARIMA framework by incorporating trigonometric (Fourier) terms as deterministic regressors. This allows the model to approximate smooth, complex, or multiple-frequency seasonal patterns without requiring a full seasonal ARIMA structure for every frequency, making it particularly useful for high-frequency data or series with non-integer or evolving seasonality.

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Sources

  1. Harvey, A., & Scott, A. (1994). Seasonality in dynamic regression models. The Economic Journal, 104(427), 1324-1345. link
  2. Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice (2nd ed.). OTexts. link

Related methods

ScholarGateFourier SARIMA model (Fourier-augmented Seasonal Autoregressive Integrated Moving Average Model). Retrieved 2026-06-04 from https://scholargate.app/tr/econometrics/fourier-sarima-model