Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Support vector quantile regression for longitudinal data

  • Received : 2010.01.03
  • Accepted : 2010.02.12
  • Published : 2010.03.31
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Abstract

Support vector quantile regression (SVQR) is capable of providing more complete description of the linear and nonlinear relationships among response and input variables. In this paper we propose a weighted SVQR for the longitudinal data. Furthermore, we introduce the generalized approximate cross validation function to select the hyperparameters which affect the performance of SVQR. Experimental results are the presented, which illustrate the performance of the proposed SVQR.

Keywords

References

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