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Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

ARIMA-modell (Autoregressiv Integrert Glidende Gjennomsnitt)×Augmented Dickey-Fuller (ADF) enhetsrot-test×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår19701979–1984
OpphavspersonGeorge Box and Gwilym JenkinsSaid & Dickey (1984); building on Dickey & Fuller (1979)
TypeTime series forecasting modelHypothesis test (unit root)
Opprinnelig kildeBox, 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 ↗
AliasARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test
Relaterte65
SammendragThe 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.
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ScholarGateSammenlign metoder: ARIMA model · Augmented Dickey-Fuller unit root test. Hentet 2026-06-15 fra https://scholargate.app/no/compare