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Forecasting using robust exponential smoothing with damped trend and seasonal components

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  • Ruben Crevits
  • Christophe Croux

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.

Suggested Citation

  • Ruben Crevits & Christophe Croux, 2017. "Forecasting using robust exponential smoothing with damped trend and seasonal components," Working Papers of Department of Decision Sciences and Information Management, Leuven 588812, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
  • Handle: RePEc:ete:kbiper:588812
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    File URL: https://lirias.kuleuven.be/retrieve/462762
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    Keywords

    Automatic Forecasting; Outliers; R package; Time series;
    All these keywords.

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