Journal of the Korean Statistical Society

  • 제33권1호
  • /
  • Pages.25-34
  • /
  • 2004
  • /
  • 1226-3192(pISSN)
  • /
  • 2005-2863(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지

REGRESSION WITH CENSORED DATA BY LEAST SQUARES SUPPORT VECTOR MACHINE

  • Kim, Dae-Hak (Department of Statistical Information, Catholic University of Daegu) ;
  • Shim, Joo-Yong (Department of Statistical Information, Catholic University of Daegu) ;
  • Oh, Kwang-Sik (Department of Statistical Information, Catholic University of Daegu)
  • 발행 : 2004.03.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper we propose a prediction method on the regression model with randomly censored observations of the training data set. The least squares support vector machine regression is applied for the regression function prediction by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed prediction method.

키워드

참고문헌

  1. The Annals of Statistics v.9 Regression analysis with randomly right censored data Koul,H.;Susarla,V.;van Ryzin,J.
  2. Philosophical Transactions of the Royal Society of London v.A209 Functions of positive and regative type, and their connection with the theory of integral equations Mercer,J.
  3. Neural Processing Letters v.9 Least square support vector machine classifier Suykens,J.A.K.;Vandewalle,J.
  4. The Nature of Statistical Learning Theory Vapnik,V.N.
  5. Statistical Learning Theory Vapnik,V.N.
  6. Biometrika v.79 M-estimation in censored linear models Zhou,M.