Support vector machine quantile regression approach for functional data: Simulation and application studies

Christophe Crambes, Ali Gannoun and Yousri Henchiri

Journal of Multivariate Analysis, 2013, vol. 121, issue C, 50-68

Abstract: The topic of this paper is related to quantile regression when the covariate is a function. The estimator we are interested in, based on the Support Vector Machine method, was introduced in Crambes et al. (2011) [11]. We improve the results obtained in this former paper, giving a rate of convergence in probability of the estimator. In addition, we give a practical method to construct the estimator, solution of a penalized L1-type minimization problem, using an Iterative Reweighted Least Squares procedure. We evaluate the performance of the estimator in practice through simulations and a real data set study.

Keywords: Conditional quantile regression; Functional covariate; Iterative reweighted least squares; Reproducing kernel Hilbert space; Support vector machine (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:121:y:2013:i:c:p:50-68

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DOI: 10.1016/j.jmva.2013.06.004

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