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Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Modelul ARIMA (Autoregresiv Integrat cu Medii Mobile)×Modelul Vectorial de Corecție a Erorii (VECM)×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției20151987
Autorul originalBox & Jenkins (Box-Jenkins methodology)Engle & Granger
TipUnivariate time-series modelMultivariate time-series model
Sursa seminalăBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276. DOI ↗
Denumiri alternativeBox-Jenkins model, ARIMA(p,d,q), ARIMA Modelivector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli)
Înrudite54
RezumatARIMA 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 Vector Error Correction Model is a multivariate time-series model for cointegrated series that captures both their short-run dynamics and their long-run equilibrium relationship. It was introduced by Engle and Granger in 1987 as part of the cointegration and error-correction framework.
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ScholarGateCompară metode: ARIMA · VECM. Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare