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Linganisha mbinu

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Kipimo cha Engle-Granger cha Uko-na-uhusiano×Mfumo wa ARIMA (Autoregressive Integrated Moving Average)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili19871970
MwanzilishiRobert F. Engle and Clive W. J. GrangerGeorge Box and Gwilym Jenkins
AinaCointegration testTime series forecasting model
Chanzo asiliaEngle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
Majina mbadalaEG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG testARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Zinazohusiana56
MuhtasariThe Engle-Granger two-step method tests whether two or more non-stationary I(1) time series share a common stochastic trend — that is, whether a linear combination of them is stationary. If cointegration is confirmed, an error-correction model (ECM) can be estimated to capture both short-run dynamics and long-run equilibrium adjustment.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.
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ScholarGateLinganisha mbinu: Engle-Granger Cointegration Test · ARIMA model. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare