Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Modelul Fourier SARIMA× | Model SARIMA× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1994 | 1970 (first edition); 1976 (revised) |
| Autorul original≠ | Harvey & Scott (1994); Hyndman & Athanasopoulos (popularization) | Box, Jenkins, and Reinsel |
| Tip≠ | Seasonal time series model with trigonometric regressors | Seasonal time series model |
| Sursa seminală≠ | Harvey, A., & Scott, A. (1994). Seasonality in dynamic regression models. The Economic Journal, 104(427), 1324-1345. link ↗ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 |
| Denumiri alternative | Fourier SARIMA, SARIMA with Fourier terms, Fourier-SARIMA, trigonometric SARIMA | SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | 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. | SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics. |
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