Robust versions of the exponential and Holt-Winters 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 robustifi ed. 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 misspecifi cation. The method is illustrated using real data incorporating trend and seasonal effects.
Gelper et al. proposed an adapted version of the classical exponential and Holt-Winters smoothing methodologies, providing them with robustness REF .
Robust Forecasting with Exponential and Holt-Winters Smoothing
Journal of Forecasting
Computer Science