@techreport{94542b5e43194f5abc35258e532d573c,
title = "Robust Forecasting of Non-Stationary Time Series",
abstract = "This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estimator. An additional advantage of the MM-estimator is that it provides a robust estimate of the local variability of the time series.",
keywords = "Heteroscedasticity, Non-parametric regression, Prediction, Outliers, Robustness",
author = "C. Croux and R. Fried and I. Gijbels and K. Mahieu",
note = "Pagination: 17",
year = "2010",
language = "English",
volume = "2010-105",
series = "CentER Discussion Paper",
publisher = "Econometrics",
type = "WorkingPaper",
institution = "Econometrics",
}