DOI QR코드

DOI QR Code

Iterative Support Vector Quantile Regression for Censored Data

  • Shim, Joo-Yong (Department of Applied Statistics, Catholic University) ;
  • Hong, Dug-Hun (Department of Mathematics, Myongji University) ;
  • Kim, Dal-Ho (Department of Statistics, Kyungbuk National University) ;
  • Hwang, Chang-Ha (Division of Information and Computer Science, Dankook University)
  • Published : 2007.04.30

Abstract

In this paper we propose support vector quantile regression (SVQR) for randomly right censored data. The proposed procedure basically utilizes iterative method based on the empirical distribution functions of the censored times and the sample quantiles of the observed variables, and applies support vector regression for the estimation of the quantile function. Experimental results we then presented to indicate the performance of the proposed procedure.

Keywords

References

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