Vertaile menetelmiä
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| ARIMA-malli (Autoregressiivinen integroitu liukuva keskiarvo)× | Augmented Dickey-Fuller (ADF) -yksikköjuuritesti× | |
|---|---|---|
| Tieteenala | Ekonometria | Ekonometria |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 1970 | 1979–1984 |
| Kehittäjä≠ | George Box and Gwilym Jenkins | Said & Dickey (1984); building on Dickey & Fuller (1979) |
| Tyyppi≠ | Time series forecasting model | Hypothesis test (unit root) |
| Alkuperäislähde≠ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ | Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607. DOI ↗ |
| Rinnakkaisnimet | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) | ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test |
| Liittyvät≠ | 6 | 5 |
| Tiivistelmä≠ | The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics. | The Augmented Dickey-Fuller test is the standard procedure for determining whether a univariate time series contains a unit root — that is, whether the series is non-stationary. It extends the original Dickey-Fuller test by including lagged difference terms that absorb serial correlation in the residuals, making the test valid for a wide range of time-series processes encountered in economics and finance. |
| ScholarGateAineisto ↗ |
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