Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель Панельной SARIMA× | Модель ARIMA (авторегрессионная интегрированная скользящая средняя)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1976 (SARIMA); 1990s (panel extensions) | 1970 |
| Автор метода≠ | Box & Jenkins (SARIMA foundation); panel extension via mean-group and pooled estimators | George Box and Gwilym Jenkins |
| Тип≠ | Seasonal time series panel model | Time series forecasting model |
| Основополагающий источник≠ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control. Holden-Day. ISBN: 978-0470272848 | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| Другие названия | Panel SARIMA, Seasonal ARIMA panel model, SARIMA panel estimation, grouped seasonal time series model | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) |
| Связанные≠ | 5 | 6 |
| Сводка≠ | The Panel SARIMA model applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) framework to panel data, fitting individual or pooled seasonal time series models across multiple cross-sectional units. It captures both non-seasonal and seasonal autocorrelation, trends, and periodicity, making it suitable for datasets where multiple entities share a common seasonal structure over time. | 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. |
| ScholarGateНабор данных ↗ |
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