文章基本信息

标题：A Method of Trend Extraction Using Singular Spectrum Analysis
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作者：Theodore Alexandrov
期刊名称：RevStat : Statistical Journal
印刷版ISSN：1645-6726
出版年度：2009
卷号：7
期号：1
页码：1-22
出版社：Instituto Nacional de Estatística
摘要：The paper presents a new method of trend extraction in the framework of the Singular Spectrum Analysis (SSA) approach. This method is easy to use, does not need specification of models of time series and trend, allows to extract trend in the presence of noise and oscillations and has only two parameters (besides basic SSA parameter called window length). One parameter manages scale of the extracted trend and another is a method specific threshold value. We propose procedures for the choice of the parameters. The presented method is evaluated on a simulated time series with a polynomial trend and an oscillating component with unknown period and on the seasonally adjusted monthly data of unemployment level in Alaska for the period 1976/01– 2006/09.
关键词：time series; trend extraction; Singular Spectrum Analysis.