方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 结构断裂季节性自回归积分移动平均模型× | SARIMA模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1970s–1998 | 1970 (first edition); 1976 (revised) |
| 提出者≠ | Box & Jenkins (SARIMA); Bai & Perron (structural break detection) | Box, Jenkins, and Reinsel |
| 类型≠ | Time series model with regime shifts | Seasonal time series model |
| 开创性文献≠ | 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 |
| 别名 | SARIMA with structural breaks, break-augmented SARIMA, piecewise SARIMA, SARIMA-SB | SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component |
| 相关≠ | 3 | 5 |
| 摘要≠ | 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. |
| ScholarGate数据集 ↗ |
|
|