Correction to: Vector Quantile Regression and Optimal Transport, from Theory to Numerics - Sciences Po Access content directly
Journal Articles Empirical Economics Year : 2022

Correction to: Vector Quantile Regression and Optimal Transport, from Theory to Numerics

Abstract

In this paper, we first revisit the Koenker and Bassett variational approach to (univariate) quantile regression, emphasizing its link with latent factor representations and correlation maximization problems. We then review the multivariate extension due to Carlier et al. (Ann Statist 44(3):1165–92, 2016,; J Multivariate Anal 161:96–102, 2017) which relates vector quantile regression to an optimal transport problem with mean independence constraints. We introduce an entropic regularization of this problem, implement a gradient descent numerical method and illustrate its feasibility on univariate and bivariate examples.

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hal-03896159 , version 1 (13-12-2022)

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Guillaume Carlier, Victor Chernozhukov, Gwendoline de Bie, Alfred Galichon. Correction to: Vector Quantile Regression and Optimal Transport, from Theory to Numerics. Empirical Economics, 2022, 62 (1), pp.63-63. ⟨10.1007/s00181-020-01933-0⟩. ⟨hal-03896159⟩
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