方法对比
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| 稳健SARIMA模型× | X-13ARIMA-SEATS 季节调整× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族≠ | Regression model | Process / pipeline |
| 起源年份≠ | 1979–2009 | 1998 |
| 提出者≠ | Muler, Peña & Yohai (robust ARMA); earlier foundation by Denby & Martin (1979) | U.S. Census Bureau; Findley et al. |
| 类型≠ | Robust time-series model | Non-parametric / model-based hybrid |
| 开创性文献≠ | Muler, N., Peña, D., & Yohai, V. J. (2009). Robust estimation for ARMA models. The Annals of Statistics, 37(2), 816–840. DOI ↗ | Findley, D. F., Monsell, B. C., Bell, W. R., Otto, M. C., & Chen, B.-C. (1998). New capabilities and methods of the X-12-ARIMA seasonal adjustment program. Journal of Business & Economic Statistics, 16(2), 127–152. DOI ↗ |
| 别名 | robust SARIMA, outlier-resistant SARIMA, robust seasonal ARIMA, M-estimator SARIMA | X-13ARIMA-SEATS, X-12-ARIMA, Census X-13, Mevsimsel Düzeltme X-13 |
| 相关≠ | 4 | 3 |
| 摘要≠ | Robust SARIMA extends the classical Seasonal ARIMA framework by replacing the standard least-squares criterion with a robust loss function — such as an M-estimator — so that outliers and heavy-tailed innovations in seasonal time series cannot distort parameter estimates or invalidate forecasts. | X-13ARIMA-SEATS is the standard seasonal adjustment program produced by the U.S. Census Bureau, combining RegARIMA pre-adjustment with either the classical X-11 filter or the model-based SEATS signal-extraction algorithm. It is the official tool used by national statistical agencies worldwide — including Eurostat and the U.S. Bureau of Labor Statistics — to remove recurring calendar and seasonal patterns from monthly or quarterly economic time series such as GDP, employment, and retail sales. |
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