مقایسهٔ روشها
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| مدل میانگین متحرک (MA)× | مدل ARMA (میانگین متحرک خودرگرسیو)× | |
|---|---|---|
| حوزه | اقتصادسنجی | اقتصادسنجی |
| خانواده | Regression model | Regression model |
| سال پیدایش | 1970 | 1970 |
| پدیدآور≠ | Box and Jenkins | George E. P. Box and Gwilym M. Jenkins |
| نوع≠ | Linear time series model | Time series model |
| منبع بنیادین≠ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| نامهای دیگر | MA model, MA(q) process, moving-average process, Box-Jenkins MA | ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q) |
| مرتبط | 5 | 5 |
| خلاصه≠ | The Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods. | The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting. |
| ScholarGateمجموعهداده ↗ |
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