Affordable Access

Nonparametric Multiple-Output Center-Outward Quantile Regression

Authors
  • Del Barrio, Eustasio
  • González-Sanz, Alberto
  • Hallin, Marc
Publication Date
Apr 25, 2022
Source
HAL
Keywords
Language
English
License
Unknown
External links

Abstract

Based on the novel concept of multivariate center-outward quantiles introduced recently in Chernozhukov et al. (2017) and Hallin et al. (2021), we are considering the problem of nonparametric multiple-output quantile regression. Our approach defines nested conditional center-outward quantile regression contours and regions with given conditional probability content irrespective of the underlying distribution; their graphs constitute nested center-outward quantile regression tubes. Empirical counterparts of these concepts are constructed, yielding interpretable empirical regions and contours which are shown to consistently reconstruct their population versions in the Pompeiu-Hausdorff topology. Our method is entirely non-parametric and performs well in simulations including heteroskedasticity and nonlinear trends; its power as a data-analytic tool is illustrated on some real datasets.

Report this publication

Statistics

Seen <100 times