Robust Forecasting with Exponential and Holt-Winters Smoothing
Robust Forecasting with Exponential and Holt-Winters Smoothing
复制标题
DOI：
10.2139/ssrn.1089403
复制
发表时间：
2007-06
期刊：
影响因子：
--
通讯作者：
S. Gelper;R. Fried;C. Croux
中科院分区：
文献类型：
--
作者：
S. Gelper;R. Fried;C. Croux
稳健版本的指数和霍尔特-温特斯平滑预测方法。它们适用于预测存在异常值的单变量时间序列。鲁棒指数和Holt-Winters平滑方法作为递归更新方案，将标准技术应用于预清洁数据。更新方程和平滑参数的选择都是鲁棒的。仿真研究比较了鲁棒预测和经典预测。所提出的方法被发现有良好的预测性能的时间序列和无异常值，以及厚尾时间序列和模型误设定。该方法说明使用真实的数据，结合趋势和季节性影响。版权所有© 2009约翰威利父子有限公司。
Robust versions of the exponential and Holt-Winters smoothing method for forecasting are presented. They are suitable for forecasting univariate time series in the presence of outliers. The robust exponential and Holt-Winters smoothing methods are presented as recursive updating schemes that apply the standard technique to pre-cleaned data. Both the update equation and the selection of the smoothing parameters are robustified. A simulation study compares the robust and classical forecasts. The presented method is found to have good forecast performance for time series with and without outliers, as well as for fat-tailed time series and under model misspecification. The method is illustrated using real data incorporating trend and seasonal effects. Copyright © 2009 John Wiley & Sons, Ltd.