Sparse quantile regression
From MaRDI portal
Publication:6108347
DOI10.1016/j.jeconom.2023.02.014arXiv2006.11201MaRDI QIDQ6108347
Publication date: 29 June 2023
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.11201
quantile regressionHamming distancefinite sample propertysparse estimationmixed integer optimizationconformal prediction
Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Nearly unbiased variable selection under minimax concave penalty
- Smooth minimization of non-smooth functions
- Best subset selection via a modern optimization lens
- The \(L_1\) penalized LAD estimator for high dimensional linear regression
- Statistics for high-dimensional data. Methods, theory and applications.
- Risk bounds for statistical learning
- Globally adaptive quantile regression with ultra-high dimensional data
- One-step sparse estimates in nonconcave penalized likelihood models
- A Bennett concentration inequality and its application to suprema of empirical processes
- Best subset binary prediction
- High dimensional censored quantile regression
- Oracle inequalities for sparse additive quantile regression in reproducing kernel Hilbert space
- Variable selection with Hamming loss
- On the conditions used to prove oracle results for the Lasso
- Sparse high-dimensional regression: exact scalable algorithms and phase transitions
- \(\ell_1\)-penalized quantile regression in high-dimensional sparse models
- Adaptive robust variable selection
- Strong oracle optimality of folded concave penalized estimation
- Efficient semiparametric estimation of multi-valued treatment effects under ignorability
- Smoothed quantile regression with large-scale inference
- Regression Quantiles
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Oracle Estimation of a Change Point in High-Dimensional Quantile Regression
- Wild residual bootstrap inference for penalized quantile regression with heteroscedastic errors
- Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension
- Binary classification with covariate selection through ℓ0-penalised empirical risk minimisation
- Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms
- Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models
- Uniform post-selection inference for least absolute deviation regression and other Z-estimation problems
- Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls
- Demystifying the Integrated Tail Probability Expectation Formula
This page was built for publication: Sparse quantile regression