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A study on a composite support vector quantile regression with varying coefficient model
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논문 기본 정보

Type
Academic journal
Author
Insuk Sohn (Samsung Medical Center) Jooyong Shim (Inje University) Kyungha Seok (Inje University)
Journal
The Korean Data and Information Science Society Journal of the Korean Data And Information Science Society Vol.29 No.4 KCI Excellent Accredited Journal
Published
2018.7
Pages
1,077 - 1,086 (10page)
DOI
10.7465/jkdi.2018.29.4.1077

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A study on a composite support vector quantile regression with varying coefficient model
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Abstract· Keywords

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Varying coefficient models are widely used to explore dynamic patterns of regression parameters among regression models available to avoid the curse of dimensionality. In this paper we propose a new regression estimation of the varying coefficient composite support vector quantile regression which combines the formulations of the composite quantile regression and the varyng coefficient support vector quantile regression which is a nonparametric quantile regression with varying regression quantiles. We also consider a cross validation method for the optimal values of hyperparameters which affect the performance of the proposed method. Numerical studies with synthetic and real data are conducted to illustrate the performance of the proposed estimation of the regression functions.

Contents

Abstract
1. Introduction
2. Varying coefficient support vector quantile regression
3. Varying coefficient composite support vector quantile regression
4. Numerical studies
5. Conclusions
References

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UCI(KEPA) : I410-ECN-0101-2018-041-003350489