Nonparametric Multiple-Output Center-Outward Quantile Regression-Reference-Cited by-同舟云学术

Nonparametric Multiple-Output Center-Outward Quantile Regression

Published:2024-06-11 Issue: Volume: Page:1-43
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

del Barrio Eustasio¹,González Sanz Alberto²,Hallin Marc³⁴^ORCID

Affiliation:

1. IMUVA, Universidad de Valladolid, Spain

2. Department of Statistics, Columbia University, New York

3. ECARES and Départment de Mathématique, Université libre de Bruxelles, Belgium

4. Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2024.2366029

Reference54 articles.

1. (2024). Multivariate Quantiles: Geometric and Measure-Transportation-Based Contours. Springer; Available at https://arxiv.org/abs/2401.02499.

2. Agarwal G. W. Tu Y. Sun and L. Kong (2022). Flexible quantile contour estimation for multivariate functional data: Beyond convexity. Computational Statistics and Data Analysis 168 107400.

3. Breckling J. and R. Chambers (1988). m-Quantiles. Biometrika 75 761–771.

4. Camehl A. D. Fok and K. Gruber (2022 December). Multivariate quantile regression using superlevel sets of conditional densities. Tinbergen Institute Discussion Papers 22-094/III Tinbergen Institute.

5. Carlier G. V. Chernozhukov and A. Galichon (2016). Vector quantile regression: an optimal transport approach. Annals of Statistics 44 1165–1192.

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