方法证据记录
Robust SARIMA model
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Robust Seasonal Autoregressive Integrated Moving Average Model
分类方法记录 · regression-model / econometrics
- Muler, N., Peña, D., & Yohai, V. J. (2009). Robust estimation for ARMA models. The Annals of Statistics, 37(2), 816–840. · DOI 10.1214/07-AOS570
- Franses, P. H., & Ghijsels, H. (1999). Additive outliers, GARCH and forecasting volatility. International Journal of Forecasting, 15(1), 1–9. · DOI 10.1016/S0169-2070(98)00053-3
精选声明
声明已持久化到证据分类账中，每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时，此视图不会自行创建声明评估。
相关方法
从方法图中生成，显示为机器建议的关系 — 不推断任何证据声明。