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Robust ARMA-model

Den robuste ARMA-model udvider det klassiske Autoregressive Moving Average-framework ved at erstatte det følsomme mindste-kvadraters tab med outlier-resistente estimeringsmetoder — typisk M-estimatorer eller medianbaserede tilgange. Dette beskytter koefficientestimater og prognoser mod at blive forvrænget af additive outliers, niveauændringer eller innovationsoutliers, som er almindelige i økonomiske og finansielle tidsserier.

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Kilder

  1. Franses, P. H., & Ghijsels, H. (1999). Additive outliers, GARCH and forecasting volatility. International Journal of Forecasting, 15(1), 1-9. link
  2. Martin, R. D., & Yohai, V. J. (1986). Influence functionals for time series. The Annals of Statistics, 14(3), 781-818. link

Sådan citerer du denne side

ScholarGate. (2026, June 3). Robust Autoregressive Moving Average Model. ScholarGate. https://scholargate.app/da/econometrics/robust-arma-model

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Refereret af

ScholarGateRobust ARMA Model (Robust Autoregressive Moving Average Model). Hentet 2026-06-15 fra https://scholargate.app/da/econometrics/robust-arma-model · Datasæt: https://doi.org/10.5281/zenodo.20539026