Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Fourier SARIMA modelis× | Fjēra VAR modelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1994 | 2010s |
| Autors≠ | Harvey & Scott (1994); Hyndman & Athanasopoulos (popularization) | Enders & Lee; extended by Nazlioglu and others to VAR systems |
| Tips≠ | Seasonal time series model with trigonometric regressors | Multivariate time-series model |
| Pirmavots≠ | Harvey, A., & Scott, A. (1994). Seasonality in dynamic regression models. The Economic Journal, 104(427), 1324-1345. link ↗ | 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 ↗ |
| Citi nosaukumi | Fourier SARIMA, SARIMA with Fourier terms, Fourier-SARIMA, trigonometric SARIMA | Fourier VAR, smooth structural break VAR, trigonometric VAR, Fourier-augmented VAR |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | 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. | The Fourier VAR model extends the standard Vector Autoregression by replacing fixed deterministic terms with Fourier trigonometric components, allowing the intercept (and optionally the trend) to shift gradually and smoothly over time. This eliminates the need to pre-specify the number, timing, or shape of structural breaks in a multivariate time-series system. |
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