مقایسهٔ روشها
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| مدل آریما (میانگین متحرک یکپارچه خودرگرسیو)× | آزمون علیت گرنجر× | |
|---|---|---|
| حوزه | اقتصادسنجی | اقتصادسنجی |
| خانواده | Regression model | Regression model |
| سال پیدایش≠ | 2015 | 1969 |
| پدیدآور≠ | Box & Jenkins (Box-Jenkins methodology) | Clive W. J. Granger |
| نوع≠ | Univariate time-series model | Time-series predictive causality test |
| منبع بنیادین≠ | 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 | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗ |
| نامهای دیگر≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi |
| مرتبط | 5 | 5 |
| خلاصه≠ | 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). | The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause. |
| ScholarGateمجموعهداده ↗ |
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