Forecasting using robust exponential smoothing with damped trend and seasonal components

Ruben Crevits and Christophe Croux

No 588812, Working Papers of Department of Decision Sciences and Information Management, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven

Abstract: We provide a framework for robust exponential smoothing. For a class of exponential smoothing variants, we present a robust alternative. The class includes models with a damped trend and/or seasonal components. We provide robust forecasting equations, robust starting values, robust smoothing parameter estimation and a robust information criterion. The method is implemented in the R package robets, allowing for automatic forecasting. We compare the standard non-robust version with the robust alternative in a simulation study. Finally, the methodology is tested on data.

Keywords: Automatic Forecasting; Outliers; R package; Time series (search for similar items in EconPapers)
Date: 2017-08
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Published in FEB Research Report KBI_1714

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Persistent link: https://EconPapers.repec.org/RePEc:ete:kbiper:588812

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