Nonparametric Quantile Regression for Banach-Valued Response

Authored by: Joydeep Chowdhury , Probal Chaudhuri

Handbook of Quantile Regression

Print publication date:  October  2017
Online publication date:  October  2017

Print ISBN: 9781498725286
eBook ISBN: 9781315120256
Adobe ISBN:

10.1201/9781315120256-14

 Download Chapter

 

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.

 Cite
Search for more...
Back to top

Use of cookies on this website

We are using cookies to provide statistics that help us give you the best experience of our site. You can find out more in our Privacy Policy. By continuing to use the site you are agreeing to our use of cookies.