Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель Панельной SARIMA× | Панельная модель ARIMA× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1976 (SARIMA); 1990s (panel extensions) | 1970s–2000s |
| Автор метода≠ | Box & Jenkins (SARIMA foundation); panel extension via mean-group and pooled estimators | Extension of Box-Jenkins ARIMA (Box & Jenkins, 1970) to panel settings; formalised in panel econometrics literature (Hsiao, 2003) |
| Тип≠ | Seasonal time series panel model | Time-series model applied to panel data |
| Основополагающий источник≠ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control. Holden-Day. ISBN: 978-0470272848 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Другие названия | Panel SARIMA, Seasonal ARIMA panel model, SARIMA panel estimation, grouped seasonal time series model | Panel ARIMA, ARIMA for panel data, cross-sectional ARIMA, multi-unit ARIMA |
| Связанные | 5 | 5 |
| 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 Panel ARIMA model extends the classical Box-Jenkins ARIMA framework to panel data, fitting autoregressive integrated moving-average dynamics to multiple cross-sectional units observed over time. It accommodates unit-specific short-run dynamics and non-stationarity, making it suitable for forecasting and dynamic analysis when both cross-sectional and temporal dimensions are present. |
| ScholarGateНабор данных ↗ |
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