مقایسهٔ روشها
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| مدل آریما (میانگین متحرک یکپارچه خودرگرسیو)× | مدل SARIMA (Seasonal ARIMA)× | |
|---|---|---|
| حوزه | اقتصادسنجی | اقتصادسنجی |
| خانواده | Regression model | Regression model |
| سال پیدایش | 2015 | 2015 |
| پدیدآور≠ | Box & Jenkins (Box-Jenkins methodology) | Box & Jenkins (seasonal extension of ARIMA) |
| نوع≠ | Univariate time-series model | Seasonal time-series model |
| 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 | 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 |
| نامهای دیگر | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | seasonal ARIMA, Box-Jenkins seasonal model, SARIMA — Mevsimsel ARIMA |
| 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). | SARIMA is a seasonal extension of the Box-Jenkins ARIMA model that adds seasonal differencing and seasonal autoregressive and moving-average terms. Developed within the Box, Jenkins, Reinsel and Ljung framework (5th edition, 2015), it forecasts series whose pattern repeats on a yearly, monthly, or weekly period. |
| ScholarGateمجموعهداده ↗ |
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