Regression modelEconometrics / time series
Fourier Moving Average (Fourier MA) Model
The Fourier MA model combines a Moving Average (MA) error structure with Fourier series terms — sine and cosine pairs — to capture complex or high-frequency seasonal patterns in time series data. It is particularly useful when the seasonal period is long or irregular, making classical seasonal ARIMA parameterisation infeasible.
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Sources
- Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts. link ↗
- Harvey, A. C. (1993). Time Series Models (2nd ed.). MIT Press. ISBN: 978-0262082242