A combination selection algorithm on forecasting

Cang, Shuang; Yu, Hongnian

Abstract

It is widely accepted in forecasting that a combination model can improve forecasting accuracy. One important challenge is how to select the optimal subset of individual models from all available models without having to try all possible combinations of these models. This paper proposes an optimal subset selection algorithm from all individual models using information theory. The experimental results in tourism demand forecasting demonstrate that the combination of the individual models from the selected optimal subset significantly outperforms the combination of all available individual models. The proposed optimal subset selection algorithm provides a theoretical approach rather than experimental assessments which dominate literature.

Citation

Cang, S., & Yu, H. (2014). A combination selection algorithm on forecasting. European Journal of Operational Research, 234(1), 127-139. https://doi.org/10.1016/j.ejor.2013.08.045

• Journal Article Type: Article
• Acceptance Date: Aug 27, 2013
• Online Publication Date: Sep 8, 2013
• Publication Date: 2014-04
• Deposit Date: Oct 23, 2019
• Publicly Available Date: Oct 23, 2019
• Journal: European Journal of Operational Research
• Print ISSN: 0377-2217
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 234
• Issue: 1
• Pages: 127-139
• DOI: https://doi.org/10.1016/j.ejor.2013.08.045
• Public URL: http://researchrepository.napier.ac.uk/Output/2246999