Usporedite metode
Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.
| Model ARIMA (Autoregresivni integrirani pokretni prosjek)× | Test Phillips-Perron (PP)× | |
|---|---|---|
| Područje | Ekonometrija | Ekonometrija |
| Obitelj | Regression model | Regression model |
| Godina nastanka≠ | 2015 | 1988 |
| Tvorac≠ | Box & Jenkins (Box-Jenkins methodology) | Peter C. B. Phillips & Pierre Perron |
| Vrsta≠ | Univariate time-series model | Unit-root test for stationarity |
| Temeljni izvor≠ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Drugi nazivi | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | PP test, Phillips-Perron unit root test, Phillips-Perron birim kök testi |
| Srodne≠ | 5 | 4 |
| Sažetak≠ | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | The Phillips-Perron test, proposed by Peter Phillips and Pierre Perron in 1988, tests for a unit root in a time series, like the Augmented Dickey-Fuller test, but corrects for autocorrelation and heteroskedasticity in the errors non-parametrically rather than by adding lagged differences. It runs a simple Dickey-Fuller regression and then adjusts the test statistic using a long-run variance estimate, so the practitioner need not choose a lag length for the regression itself. |
| ScholarGateSkup podataka ↗ |
|
|