Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Furjē-Perrona (Fourier PP) vienības saknes tests× | Fjūrjēra KPSS stacionaritātes tests ar vienmērīgām strukturālām pārmaiņām× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads | 2006 | 2006 |
| Autors | Becker, Enders, and Lee | Becker, Enders, and Lee |
| Tips≠ | Unit root test with Fourier approximation | Stationarity test |
| Pirmavots≠ | Enders, W., & Siklos, P. L. (2001). Cointegration and threshold adjustment. Journal of Business and Economic Statistics, 19(2), 166-176. DOI ↗ | Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗ |
| Citi nosaukumi | Fourier PP test, Flexible Fourier PP unit root test, Enders-Lee Fourier PP test, nonlinear PP unit root test | Fourier KPSS, flexible Fourier stationarity test, F-KPSS, KPSS with Fourier approximation |
| Saistītās≠ | 6 | 3 |
| Kopsavilkums≠ | The Fourier PP unit root test extends the classical Phillips-Perron test by embedding low-frequency Fourier terms in the deterministic component, enabling the test to account for an unknown number of smooth, gradual structural breaks in the level or trend without pre-specifying their timing or shape. | The Fourier KPSS test extends the standard KPSS stationarity test by embedding a flexible Fourier series in the deterministic component of the model. This approach captures smooth, gradual structural breaks in the level or trend of a time series without requiring the researcher to specify the number or timing of those breaks, yielding more reliable inference under structural change. |
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