The theta model: a decomposition approach to forecasting
The theta model: a decomposition approach to forecasting
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DOI：
10.1016/s0169-2070(00)00066-2
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发表时间：
2000-10-01
影响因子：
7.9
通讯作者：
Nikolopoulos, K
中科院分区：
文献类型：
--
作者：
Assimakopoulos, V;Nikolopoulos, K
本文提出了一种新的单变量预测方法。该方法是基于修改的局部曲率的时间序列的概念，通过一个系数'Theta'（希腊字母theta），这是直接适用于第二个差异的数据。创建的结果系列保留原始数据的平均值和斜率，但不保留其曲率。这些新的时间序列被命名为Theta线。它们的主要定性特征是数据的长期行为的近似的改进或短期特征的增强，这取决于Theta系数的值。该方法将原始时间序列分解为两个或多个不同的Theta线。该等预测乃分别推算，其后之预测则合并计算。两条θ线的简单组合，θ = 0（直线）和θ = 2（双局部曲线）被采用，以产生对M3比赛的3003系列的预测。该方法表现良好，特别是对月度系列和微观经济数据。(C)2000 Elsevier Science B.V.保留所有权利。
This paper presents a new univariate forecasting method. The method is based on the concept of modifying the local curvature of the time-series through a coefficient 'Theta' (the Greek letter theta), that is applied directly to the second differences of the data. The resulting series that are created maintain the mean and the slope of the original data but not their curvatures. These new time series are named Theta-lines. Their primary qualitative characteristic is the improvement of the approximation of the long-term behavior of the data or the augmentation of the short-term features, depending on the value of the Theta coefficient. The proposed method decomposes the original time series into two or more different Theta-lines. These are extrapolated separately and the subsequent forecasts are combined. The simple combination of two Theta-lines, the Theta = 0 (straight line) and Theta = 2 (double local curves) was adopted in order to produce forecasts for the 3003 series of the M3 competition. The method performed well, particularly for monthly series and for microeconomic data. (C) 2000 Elsevier Science B.V. All rights reserved.