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Modelo ARIMA (Autoregressive Integrated Moving Average)×Teste de Raiz Unitária Aumentado de Dickey-Fuller (ADF)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem19701979–1984
Autor originalGeorge Box and Gwilym JenkinsSaid & Dickey (1984); building on Dickey & Fuller (1979)
TipoTime series forecasting modelHypothesis test (unit root)
Fonte seminalBox, 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 ↗
Outros nomesARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test
Relacionados65
ResumoThe 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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ScholarGateComparar métodos: ARIMA model · Augmented Dickey-Fuller unit root test. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare