Single-index composite quantile regression for ultra-high-dimensional data

Author:

Jiang Rong,Sun Mengxian

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference38 articles.

1. Belloni A, Chernozhukov V, Kato K (2011) $$l_1$$-penalized quantile regression in high-dimensional sparse models. Ann Stat 39:82–130

2. Belloni A, Chernozhukov V, Kato K (2013) Robust inference in high-dimensional approximately sparse quantile regression models. arXiv:1312.7186

3. Bradic J, Kolar M (2017) Uniform inference for high-dimensional quantile regression: linear functionals and regression rank scores. arXiv:1702.06209

4. Cai TT, Liu W, Luo X (2011) A constrained $$l_1$$ minimization approach to sparse precision matrix estimation. J Am Stat Assoc 106:594–607

5. Chen X, Liu W, Mao X, Yang Z (2020) Distributed high-dimensional regression under a quantile loss function. J Mach Learn Res 21:1–43

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