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| Fourier AR model× | ARIMA model (Autoregressive Integrated Moving Average)× | |
|---|---|---|
| Područje | Ekonometrija | Ekonometrija |
| Obitelj | Regression model | Regression model |
| Godina nastanka≠ | 2012 | 1970 |
| Tvorac≠ | Enders & Lee | George Box and Gwilym Jenkins |
| Vrsta≠ | Time series model with Fourier augmentation | Time series forecasting model |
| Temeljni izvor≠ | Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574–599. DOI ↗ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| Drugi nazivi | Fourier AR, trigonometric AR model, smooth transition AR with Fourier terms, FAR model | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) |
| Srodne | 6 | 6 |
| Sažetak≠ | The Fourier AR model extends the standard autoregressive specification by adding trigonometric (sine and cosine) terms to the deterministic component. This allows the model to capture smooth, gradual shifts in the mean or trend of a time series without requiring the researcher to locate or count structural break points explicitly. | The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics. |
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