Fast Algorithm for Penalized Quantile Regression

Implements an efficient algorithm for fitting the entire regularization path of quantile regression models with elastic-net penalties using a generalized coordinate descent scheme. The framework also supports SCAD and MCP penalties. It is designed for high-dimensional datasets and emphasizes numerical accuracy and computational efficiency. This package implements the algorithms proposed in Tang, Q., Zhang, Y., & Wang, B. (2022) < https://openreview.net/pdf?id=RvwMTDYTOb>.


Reference manual

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install.packages("hdqr")

1.0.2 by Qian Tang, a year ago


Browse source code at https://github.com/cran/hdqr


Authors: Qian Tang [aut, cre] , Yikai Zhang [aut] , Boxiang Wang [aut]


Documentation:   PDF Manual  


GPL-2 license


Imports stats, Matrix, methods

Suggests knitr, rmarkdown


Imported by QuanDA.


See at CRAN