قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| نموذج ARIMA (الانحدار الذاتي المتكامل المتوسط المتحرك)× | نموذج المتوسط المتحرك (MA)× | |
|---|---|---|
| المجال | الاقتصاد القياسي | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة | 1970 | 1970 |
| صاحب الطريقة≠ | George Box and Gwilym Jenkins | Box and Jenkins |
| النوع≠ | Time series forecasting model | Linear time series model |
| المصدر التأسيسي≠ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 |
| الأسماء البديلة | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) | MA model, MA(q) process, moving-average process, Box-Jenkins MA |
| ذات صلة≠ | 6 | 5 |
| الملخص≠ | 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. | 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. |
| ScholarGateمجموعة البيانات ↗ |
|
|