قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| نموذج المتوسط المتحرك (MA)× | نموذج ARIMA (الانحدار الذاتي المتكامل المتوسط المتحرك)× | |
|---|---|---|
| المجال | الاقتصاد القياسي | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة | 1970 | 1970 |
| صاحب الطريقة≠ | Box and Jenkins | George Box and Gwilym Jenkins |
| النوع≠ | Linear time series model | Time series forecasting model |
| المصدر التأسيسي≠ | 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 ↗ |
| الأسماء البديلة | MA model, MA(q) process, moving-average process, Box-Jenkins MA | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) |
| ذات صلة≠ | 5 | 6 |
| الملخص≠ | 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 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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