Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Variance function estimation with LS-SVM for replicated data

  • Shim, Joo-Yong (Department of Applied Statistics, Catholic University of Daegu) ;
  • Park, Hye-Jung (Division of General Education and Teacher's Certification, Daegu University) ;
  • Seok, Kyung-Ha (Department of Data Science, Institute of Statistical Information, Inje University)
  • Published : 2009.09.30
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Abstract

In this paper we propose a variance function estimation method for replicated data based on averages of squared residuals obtained from estimated mean function by the least squares support vector machine. Newton-Raphson method is used to obtain associated parameter vector for the variance function estimation. Furthermore, the cross validation functions are introduced to select the hyper-parameters which affect the performance of the proposed estimation method. Experimental results are then presented which illustrate the performance of the proposed procedure.

Keywords

References

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