Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Vektorivirheenkorjausmalli (VECM)× | ARIMA (Autoregressive Integrated Moving Average) -malli× | |
|---|---|---|
| Tieteenala | Ekonometria | Ekonometria |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 1987 | 2015 |
| Kehittäjä≠ | Engle & Granger | Box & Jenkins (Box-Jenkins methodology) |
| Tyyppi≠ | Multivariate time-series model | Univariate time-series model |
| Alkuperäislähde≠ | Engle, 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., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 |
| Rinnakkaisnimet≠ | vector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli) | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| Liittyvät≠ | 4 | 5 |
| Tiivistelmä≠ | 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. | ARIMA 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). |
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