Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Kernel method for autoregressive data

  • Shim, Joo-Yong (Department of Applied Statistics, Catholic University of Daegu) ;
  • Lee, Jang-Taek (Department of Statistics, Dankook University)
  • Published : 2009.09.30
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Abstract

The autoregressive process is applied in this paper to kernel regression in order to infer nonlinear models for predicting responses. We propose a kernel method for the autoregressive data which estimates the mean function by kernel machines. We also present the model selection method which employs the cross validation techniques for choosing the hyper-parameters which affect the performance of kernel regression. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of mean function in the presence of autocorrelation between data.

Keywords

References

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