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Correlation analysis of forecasting methods: The case of the M4 competition

机译:预测方法的相关性分析:以M4竞赛为例

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This commentary introduces a correlation analysis of the top-10 ranked forecasting methods that participated in the M4 forecasting competition. The "M" competitions attempt to promote and advance research in the field of forecasting by inviting both industry and academia to submit forecasting algorithms for evaluation over a large corpus of real-world datasets. After performing the initial analysis to derive the errors of each method, we proceed to investigate the pairwise correlations among them in order to understand the extent to which they produce errors in similar ways. Based on our results, we conclude that there is indeed a certain degree of correlation among the top 10 ranked methods, largely due to the fact that many of them consist of a combination of well-known, statistical and machine learning techniques. This fact has a strong impact on the results of the correlation analysis, and therefore leads to similar forecasting error patterns. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
机译:本评论介绍了参与M4预测竞赛的排名前10位的预测方法的相关性分析。 “ M”竞赛试图通过邀请行业和学术界提交预测算法来对大型现实数据集进行评估,从而促进和推进预测领域的研究。在执行初始分析以得出每种方法的误差之后,我们继续研究它们之间的成对相关性,以了解它们以类似方式产生误差的程度。根据我们的结果,我们得出结论,排名前10位的方法之间确实存在一定程度的相关性,这主要是由于其中许多方法是由众所周知的统计技术和机器学习技术组成的。这个事实对相关分析的结果有很大的影响,因此导致相似的预测误差模式。 (C)2019国际预报员学会。由Elsevier B.V.发布。保留所有权利。

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