Quantile regression by dyadic CART-Reference-Cited by-同舟云学术

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Quantile regression by dyadic CART

Published:2024-01-01 Issue:1 Volume:18 Page:
ISSN:1935-7524
Container-title:Electronic Journal of Statistics
language:
Short-container-title:Electron. J. Statist.

Author:

Madrid Padilla Oscar Hernan¹,Chatterjee Sabyasachi²

Affiliation:

1. Department of Statistics University of California, Los Angeles 520 Portola Plaza, Los Angeles, California 90095, U.S.A

2. Department of Statistics University of Illinois at Urbana-Champaign 725 S. Wright St. M/C 374, Champaign, Illinois 61820, U.S.A

Publisher

Institute of Mathematical Statistics

Reference41 articles.

1. Laura Jula Vanegas, Merle Behr, and Axel Munk. Multiscale quantile segmentation. Journal of the American Statistical Association, pages 1–14, 2021.

2. David L Donoho. Cart and best-ortho-basis: a connection. The Annals of Statistics, 25(5):1870–1911, 1997.

3. Susan Athey, Julie Tibshirani, and Stefan Wager. Generalized random forests. The Annals of Statistics, 47(2):1148–1178, 2019.

4. Alexandre Belloni and Victor Chernozhukov. $ℓ_{1}$ -penalized quantile regression in high-dimensional sparse models. The Annals of Statistics, 39(1):82–130, 2011.

5. JiaWang Bian, Wen-Yan Lin, Yasuyuki Matsushita, Sai-Kit Yeung, Tan-Dat Nguyen, and Ming-Ming Cheng. Gms: Grid-based motion statistics for fast, ultra-robust feature correspondence. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4181–4190, 2017.

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