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  • 标题:The SVM Approach for Box–Jenkins Models
  • 本地全文:下载
  • 作者:Saeid Amiri ; Dietrich von Rosen ; Silvelyn Zwanzig.
  • 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:23-36
  • 出版社:Instituto Nacional de Estatística
  • 摘要:Support Vector Machine (SVM) is known in classification and regression modeling. It has been receiving attention in the application of nonlinear functions. The aim is to motivate the use of the SVM approach to analyze the time series models. This is an effort to assess the performance of SVM in comparison with ARMA model. The applicability of this approach for a unit root situation is also considered.
  • 关键词:Support Vector Machine; time series analysis; unit root.
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