文章基本信息

标题：Robust time series models with trend and seasonal components
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作者：Michele Caivano ; Andrew Harvey ; Alessandra Luati 等
期刊名称：SERIEs: Journal of the Spanish Economic Association
印刷版ISSN：1869-4187
电子版ISSN：1869-4195
出版年度：2016
卷号：7
期号：1
页码：99-120
DOI：10.1007/s13209-015-0134-1
出版社：Springer Berlin / Heidelberg
摘要：We describe observation driven time series models for Student-t and EGB2 conditional distributions in which the signal is a linear function of past values of the score of the conditional distribution. These specifications produce models that are easy to implement and deal with outliers by what amounts to a soft form of trimming in the case of t and a soft form of Winsorizing in the case of EGB2. We show how a model with trend and seasonal components can be used as the basis for a seasonal adjustment procedure. The methods are illustrated with US and Spanish data.
关键词：Fat tails ; EGB2 ; Score ; Robustness ; Student’s t ; Trimming ; Winsorizing