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Vector quantile regression and optimal transport, from theory to numerics

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 نشر من قبل Alfred Galichon
 تاريخ النشر 2021
  مجال البحث اقتصاد مالية
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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. (2016, 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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