Regression modelEconometrics / time series

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.

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Sources

  1. 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
  2. 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

Related methods

ScholarGateRobust SARIMA model (Robust Seasonal Autoregressive Integrated Moving Average Model). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/robust-sarima-model