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  • IJF 2019 SCUM (post-print)

    Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Forecasting. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Forecasting, ?, ?, 2019 DOI: 10.1016/j.ijforecast.2019.01.006

    Accepted author manuscript, 312 KB, PDF document

    Embargo ends: 17/04/21

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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A Simple Combination of Univariate Models

Research output: Contribution to journalJournal article

E-pub ahead of print
<mark>Journal publication date</mark>17/04/2019
<mark>Journal</mark>International Journal of Forecasting
Publication statusE-pub ahead of print
Early online date17/04/19
Original languageEnglish

Abstract

This paper describes the approach that we implemented to produce the point forecasts and prediction intervals for the M4-competition submission. The proposed Simple Combination of Univariate Models (SCUM) is the median combination of the point forecasts and prediction intervals of four models, namely Exponential Smoothing, Complex Exponential Smoothing, Automatic Autoregressive Integrated Moving Average and Dynamic Optimised Theta. Our submission performed very well in the M4-competition, being ranked 6th for the point forecasts (with a small difference compared to the 2nd submission) and prediction intervals and 2nd and 3rd for the point forecasts of the weekly and quarterly data respectively.

Bibliographic note

This is the author’s version of a work that was accepted for publication in International Journal of Forecasting. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Forecasting, ?, ?, 2019 DOI: 10.1016/j.ijforecast.2019.01.006