Quantile regression for compositional covariates

DOI10.1080/03610918.2020.1862231arXiv2006.00789OpenAlexW3118928492MaRDI QIDQ6171518

Ping Zhang, Xue-Jun Ma

Publication date: 18 July 2023

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2006.00789

zbMATH Keywords

linear programmingquantile regressioncompositional dataadaptive Lassomean regression

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Cites Work

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• Nearly unbiased variable selection under minimax concave penalty
• Variable selection in regression with compositional covariates
• The Adaptive Lasso and Its Oracle Properties
• Limiting distributions for \(L_1\) regression estimators under general conditions
• Regression Quantiles
• Reappraising Medfly Longevity
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Sparsity and Smoothness Via the Fused Lasso
• Regularization and Variable Selection Via the Elastic Net
• Tuning parameter selectors for the smoothly clipped absolute deviation method
• ADMM for Penalized Quantile Regression in Big Data

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