Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Нелинейный тест на единичный корень Филлипса-Перрона× | Нелинейный тест KPSS× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1988 (base); 2000s (nonlinear extensions) | 2006 |
| Автор метода≠ | Phillips & Perron (1988); nonlinear extensions by Kapetanios, Shin & Snell (2003) and related authors | Becker, Enders & Lee |
| Тип≠ | Unit root test with nonlinear adjustment | Stationarity test (null: stationary) |
| Основополагающий источник≠ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. 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 ↗ |
| Другие названия | Nonlinear PP test, Nonlinear Phillips-Perron test, PP unit root test with nonlinear adjustment, nonlinear PP | KPSS nonlinearity test, nonlinear stationarity test, flexible Fourier KPSS, NL-KPSS |
| Связанные≠ | 6 | 3 |
| Сводка≠ | The Nonlinear Phillips-Perron unit root test extends the classic PP test by allowing the adjustment toward equilibrium to follow a nonlinear path — such as a smooth transition or threshold mechanism — rather than assuming a constant linear speed of adjustment. This makes it more powerful when the true data-generating process involves regime-dependent or asymmetric mean-reversion dynamics. | The nonlinear KPSS test extends the classic Kwiatkowski-Phillips-Schmidt-Shin stationarity test by modelling unknown smooth structural breaks in the deterministic trend using a Fourier approximation. Under the null hypothesis the series is stationary around a flexible nonlinear trend, guarding against spurious unit-root findings caused by regime shifts or gradual transitions. |
| ScholarGateНабор данных ↗ |
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