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Robust forecasting with exponential and Holt-Winters smoothing. (English) Zbl 1203.62164
Summary: Robust versions of the exponential and Holt-Winters [see P. R. Winters, Manage. Sci. 6, 324–342 (1960; Zbl 0995.90562)] smoothing method for forecasting are presented. They are suitable for forecasting univariate time series in the presence of outliers. The robust exponential and Holt-Winters smoothing methods are presented as recursive updating schemes that apply the standard technique to pre-cleaned data. Both the update equation and the selection of the smoothing parameters are robustified. A simulation study compares the robust and classical forecasts. The presented method is found to have good forecast performance for time series with and without outliers, as well as for fat-tailed time series and under model misspecification. The method is illustrated using real data incorporating trend and seasonal effects.

MSC:
62M20 Inference from stochastic processes and prediction
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
65C60 Computational problems in statistics (MSC2010)
Software:
robustbase
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