Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Модель SARIMA× | Модель ARMA (авторегресійна ковзна середня)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1970 (first edition); 1976 (revised) | 1970 |
| Автор методу≠ | Box, Jenkins, and Reinsel | George E. P. Box and Gwilym M. Jenkins |
| Тип≠ | Seasonal time series model | Time series model |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component | ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q) |
| Пов'язані | 5 | 5 |
| Підсумок≠ | SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics. | 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. |
| ScholarGateНабір даних ↗ |
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