Nonparametric quantile regression for banach-valued response

Document Type

Book Chapter

Publication Title

Handbook of Quantile Regression

Abstract

Quantile regression for data involving covariates that are functions has been extensively considered in the recent literature. Linear quantile regression with real response and functional covariate is considered by Kato (2012) and Cardot et al. (2005). Nonparametric quantile regression with real response and functional covariate is investigated in Ferraty and Vieu (2006) and Gardes et al. (2010). Semiparametric quantile regression with real response and functional covariate is explored in Chen and Müller (2012). Nonparametric quantile regression with finite-dimensional response and functional covariate is studied in Chaouch and Laïb (2013, (2015). The examples below illustrate how the usual mean regression or median regression, which focuses on the center of the conditional distribution, sometimes fails to detect important features in the data, while quantile regression adequately captures those. In these examples, the responses are real-valued and the covariates are functions.

First Page

225

Last Page

251

DOI

10.1201/9781315120256

Publication Date

1-1-2017

Comments

Open Access, Green

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