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Support vector quantile regression for longitudinal data  

Hwang, Chang-Ha (Department of Statistics, Dankook University)
Publication Information
Journal of the Korean Data and Information Science Society / v.21, no.2, 2010 , pp. 309-316 More about this Journal
Abstract
Support vector quantile regression (SVQR) is capable of providing more complete description of the linear and nonlinear relationships among response and input variables. In this paper we propose a weighted SVQR for the longitudinal data. Furthermore, we introduce the generalized approximate cross validation function to select the hyperparameters which affect the performance of SVQR. Experimental results are the presented, which illustrate the performance of the proposed SVQR.
Keywords
Generalized approximate cross validation function; kernel function; longitudinal data; support vector quantile regression;
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Times Cited By KSCI : 4  (Citation Analysis)
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