FHDQR

This R packages fits the penalized quantile regression via fast alternating direction method of multipliers algorithms.

Sparse Composite Quantile Regression in Ultrahigh Dimensions With Tuning Parameter Calibration

We study the sparse composite quantile regression under ultrahigh dimensionality and make theoretical and algorithmic contributions.

ADMM for High-Dimensional Sparse Penalized Quantile Regression

We propose two variants of the ADMM algorithm to solve the weighted lasso and elastic net penalized quantile regression and show they are very efficient.