[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5351/CKSS.2007.14.1.195

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)

Publication Information

Communications for Statistical Applications and Methods / v.14, no.1, 2007 , pp. 195-203 More about this Journal

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

Censoring; empirical distribution function; quantile regression; support vector regression;

Citations & Related Records

Reference

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