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| Model ARIMA (Autoregressive Integrated Moving Average)× | Prošireni Diki-Fulerov (ADF) test na jedinicu korena× | KPSS test stacionarnosti× | |
|---|---|---|---|
| Oblast | Ekonometrija | Ekonometrija | Ekonometrija |
| Porodica | Regression model | Regression model | Regression model |
| Godina nastanka≠ | 2015 | 1979 | 1992 |
| Tvorac≠ | Box & Jenkins (Box-Jenkins methodology) | David A. Dickey & Wayne A. Fuller | Kwiatkowski, Phillips, Schmidt & Shin |
| Tip≠ | Univariate time-series model | Unit-root test for stationarity | Stationarity test (reverse of unit-root tests) |
| 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 | Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431. DOI ↗ | Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1–3), 159–178. DOI ↗ |
| Drugi nazivi≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | ADF test, Dickey-Fuller test, unit root test, Genişletilmiş Dickey-Fuller testi | Kwiatkowski-Phillips-Schmidt-Shin test, stationarity test, KPSS durağanlık testi |
| Srodne≠ | 5 | 4 | 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 Augmented Dickey-Fuller (ADF) test is the most widely used test for a unit root — that is, for whether a time series is non-stationary and must be differenced before modelling. Introduced by David Dickey and Wayne Fuller in 1979 and extended by Said and Dickey in 1984 to series with higher-order autocorrelation, it regresses the change in the series on its lagged level plus lagged differences and asks whether the lagged-level coefficient is zero. | The KPSS test, introduced by Kwiatkowski, Phillips, Schmidt and Shin in 1992, tests the null hypothesis that a series is stationary against the alternative that it contains a unit root — the reverse of the ADF and Phillips-Perron tests. By flipping the burden of proof, it is designed to be used alongside unit-root tests so that the two can confirm one another and expose ambiguous, borderline cases. |
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