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A simple combination of univariate models

机译:单变量模型的简单组合

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This paper describes the approach that we implemented for producing the point forecasts and prediction intervals for our M4-competition submission. The proposed simple combination of univariate models (SCUM) is a 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. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
机译:本文介绍了为生成M4竞赛提交的分数预测和预测间隔而实施的方法。提出的单变量模型(SCUM)的简单组合是点预测和四个模型的预测间隔的中位数组合,即指数平滑,复指数平滑,自动自回归综合移动平均值和动态优化theta。我们的提交在M4竞赛中表现出色,在点预测(与第二次提交相比略有差异)和预测间隔上分别排名第六和每周和每季度数据的预测分别排名第二和第三。 (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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