Robust Forecasting of Non-Stationary Time Series
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- I. Gijbels & A. Pope & M. P. Wand, 1999. "Understanding exponential smoothing via kernel regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 39-50.
- Fried, Roland & Einbeck, Jochen & Gather, Ursula, 2007. "Weighted Repeated Median Smoothing and Filtering," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1300-1308, December.
- Sarah Gelper & Roland Fried & Christophe Croux, 2010. "Robust forecasting with exponential and Holt-Winters smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 285-300.
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