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Autoregressives Modell (AR)×Augmented Dickey-Fuller (ADF) Einheitswurzeltest×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr1970s (popularised 1976)1979–1984
UrheberGeorge E. P. Box and Gwilym M. JenkinsSaid & Dickey (1984); building on Dickey & Fuller (1979)
TypTime series modelHypothesis test (unit root)
Wegweisende QuelleBox, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607. DOI ↗
AliasnamenAR model, AR(p) model, autoregression, AR processADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test
Verwandt65
ZusammenfassungAn autoregressive model of order p — AR(p) — expresses the current value of a time series as a linear function of its own p most recent past values plus a white-noise error. It is the building block of the Box-Jenkins family of time-series models and is widely used for forecasting stationary economic and financial series.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.
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ScholarGateMethoden vergleichen: Autoregressive model · Augmented Dickey-Fuller unit root test. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare