Time Series Prediction with Periodic Kernels

  • Marcin Michalak
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 95)


This short article presents the new algorithm of time series prediction: PerKE. It implements the kernel regression for the time series directly without any data transformation. This method is based on the new type of kernel function – periodic kernel function – which two examples are also introduced in this paper. This new algorithm belongs to the group of semiparametric methods as it needs the initial step that separate the trend from the original time series.


time series prediction regression kernel methods periodic kernel functions semiparametric methods 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marcin Michalak
    • 1
    • 2
  1. 1.Central Mining InstituteKatowicePoland
  2. 2.Silesian University of TechnologyGliwicePoland

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