Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель SARIMA со структурными разрывами× | Модель SARIMA× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1970s–1998 | 1970 (first edition); 1976 (revised) |
| Автор метода≠ | Box & Jenkins (SARIMA); Bai & Perron (structural break detection) | Box, Jenkins, and Reinsel |
| Тип≠ | Time series model with regime shifts | Seasonal time series model |
| Основополагающий источник≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 |
| Другие названия | SARIMA with structural breaks, break-augmented SARIMA, piecewise SARIMA, SARIMA-SB | SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component |
| Связанные≠ | 3 | 5 |
| Сводка≠ | The Structural Break SARIMA model extends the classical Seasonal ARIMA framework by explicitly detecting and accommodating abrupt, permanent shifts in the level, trend, or seasonal pattern of a time series. Rather than forcing a single SARIMA specification across the entire sample, the model partitions the series at estimated breakpoints and fits separate SARIMA processes to each resulting segment, producing more accurate forecasts and reliable inference in the presence of regime changes. | 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. |
| ScholarGateНабор данных ↗ |
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