Other packages > Find by keyword >

hrqglas  

Group Variable Selection for Quantile and Robust Mean Regression
View on CRAN: Click here


Download and install hrqglas package within the R console
Install from CRAN:
install.packages("hrqglas")

Install from Github:
library("remotes")
install_github("cran/hrqglas")

Install by package version:
library("remotes")
install_version("hrqglas", "1.1.2")



Attach the package and use:
library("hrqglas")
Maintained by
Shaobo Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-23
Latest Update: 2025-06-12
Description:
A program that conducts group variable selection for quantile and robust mean regression (Sherwood and Li, 2022). The group lasso penalty (Yuan and Lin, 2006) is used for group-wise variable selection. Both of the quantile and mean regression models are based on the Huber loss. Specifically, with the tuning parameter in the Huber loss approaching to 0, the quantile check function can be approximated by the Huber loss for the median and the tilted version of Huber loss at other quantiles. Such approximation provides computational efficiency and stability, and has also been shown to be statistical consistent.
How to cite:
Shaobo Li (2021). hrqglas: Group Variable Selection for Quantile and Robust Mean Regression. R package version 1.1.2, https://cran.r-project.org/web/packages/hrqglas. Accessed 20 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:47), 1.0.1 (2021-08-17 00:00), 1.0 (2021-06-23 08:20), 1.1.0 (2023-01-30 09:30)
Other packages that cited hrqglas R package
View hrqglas citation profile
Other R packages that hrqglas depends, imports, suggests or enhances
Complete documentation for hrqglas
Functions, R codes and Examples using the hrqglas R package
Some associated functions: coef.cv.hrq_glasso . coef.hrq_glasso . cv.hrq_glasso . hrq_glasso . plot.cv.hrq_glasso . predict.cv.hrq_glasso . predict.hrq_glasso . 
Some associated R codes: cores.R . hrq_glasso.R . hrq_glasso_coef.R . hrq_glasso_cv.R . hrq_glasso_cv_plot.R . hrq_glasso_predict.R . utils.R .  Full hrqglas package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

Brundle  
Normalisation Tools for Inter-Condition Variability of ChIP-Seq Data
Inter-sample condition variability is a key challenge of normalising ChIP-seq data. This implementat ...
Download / Learn more Package Citations See dependency  
mapaccuracy  
Unbiased Thematic Map Accuracy and Area
Unbiased estimators of overall and per-class thematic map accuracy and area published in Olofsson et ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
AsthmaNHANES  
Asthma Data Sets from NHANES
Data sets and examples from National Health and Nutritional Examination Survey (NHANES). ...
Download / Learn more Package Citations See dependency  
matlabr  
An Interface for MATLAB using System Calls
Provides users to call MATLAB from using the "system" command. Allows users to submit lines of code ...
Download / Learn more Package Citations See dependency  
ggtea  
Palettes and Themes for 'ggplot2'
A collection of palettes and themes for 'ggplot2', offering a light, pastel aesthetic. Syntax follow ...
Download / Learn more Package Citations See dependency  

28,313

R Packages

239,283

Dependencies

75,034

Author Associations

28,314

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA