Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Strukturālās lūzuma ADF vienības saknes tests× | Filipsa-Perona saknes tests× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1989-1992 | 1988 |
| Autors≠ | Perron (1989); Zivot and Andrews (1992) | Peter C. B. Phillips and Pierre Perron |
| Tips≠ | Unit root test with structural break | Hypothesis test (unit root) |
| Pirmavots≠ | Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361-1401. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Citi nosaukumi | ADF with structural break, Perron unit root test, break-augmented ADF, unit root test with structural change | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | The structural break ADF unit root test extends the standard Augmented Dickey-Fuller test to allow for one or more discrete shifts in the level or trend of a time series. Because ignoring a structural break inflates the apparent persistence of a series, this test prevents false acceptance of the unit root null when the series is actually stationary around a shifting mean or trend. | The Phillips-Perron (PP) test is a nonparametric unit root test for time series that corrects for serial correlation and heteroscedasticity in the error term without adding lagged differences. Introduced by Phillips and Perron (1988), it applies a kernel-based long-run variance estimator to adjust the Dickey-Fuller statistic, making it robust to a wide class of weakly dependent error processes. |
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