Robust AR model
The robust AR model fits an autoregressive time series specification using estimation methods — typically M-estimators or bounded-influence estimators — that resist distortion from outliers and heavy-tailed error distributions. Unlike OLS-based AR estimation, robust variants down-weight extreme observations so that a small number of contaminated data points cannot dominate the fitted dynamics.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Martin, R. D., & Yohai, V. J. (1986). Influence functionals for time series. Annals of Statistics, 14(3), 781–818. · DOI 10.1214/aos/1176350027
- Francq, C., & Zakoian, J.-M. (2010). GARCH Models: Structure, Statistical Inference and Financial Applications. Wiley. · ISBN 978-0470683910
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Related methods
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