Forecasting Using Robust Exponential Smoothing with Damped Trend and Seasonal Components

KBI_1741

25 Pages Posted: 13 Nov 2017

See all articles by Ruben Crevits

Ruben Crevits

KU Leuven - Faculty of Business and Economics (FEB)

Christophe Croux

KU Leuven - Faculty of Business and Economics (FEB)

Date Written: August 2017

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

Suggested Citation

Crevits, Ruben and Croux, Christophe, Forecasting Using Robust Exponential Smoothing with Damped Trend and Seasonal Components (August 2017). KBI_1741, Available at SSRN: https://ssrn.com/abstract=3068634 or http://dx.doi.org/10.2139/ssrn.3068634

Ruben Crevits (Contact Author)

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Christophe Croux

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

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