Semiparametric Median Regression with Censored Data

• 발행기관: 한국자료분석학회
• 저자명: 김대학(Daehak Kim) 심주용(Jooyong Shim)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.9 No.5, 2127~2134쪽, 전체 8쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2007.10.30

영문 초록

In this paper support vector machine is used for the semiparametric median regression when the responses are subject to randomly right censoring. We divide the input vector into the linear part and the nonlinear part according to whether the functional form of its effect on the response variable is specified as linear or not. The weights formed with Kaplan-Meir estimates of censoring distribution are used for the proposed method. Experimental results are then presented which indicate the performance of the estimation method.

목차

1. Introduction

2. Median Regression with Censored Data using SVM

3. Semiparametric Median Regression with Censored Data using SVM

4. Numerical study

5. Concluding Remarks

References

키워드

Semiparametric regression Randomly right censoring Kaplan-Meir estimates Support vector machine