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 29 Sep. 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

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
FRESA.CAD  
Feature Selection Algorithms for Computer Aided Diagnosis
Contains a set of utilities for building and testing statistical models (linear, logistic,ordinal or ...
Download / Learn more Package Citations See dependency  
uniswappeR  
Interact with the Uniswap Platform
Routines to interact with the Uniswap trading platform and its API < ...
Download / Learn more Package Citations See dependency  
PMCMRplus  
Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended
For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs mul ...
Download / Learn more Package Citations See dependency  
miniMeta  
Web Application to Run Meta-Analyses
Shiny web application to run meta-analyses. Essentially a graphical front-end to package 'meta' for ...
Download / Learn more Package Citations See dependency  
CopSens  
Copula-Based Sensitivity Analysis for Observational Causal Inference
Implements the copula-based sensitivity analysis method, as discussed in Copula-based Sensitivity A ...
Download / Learn more Package Citations See dependency  

28,833

R Packages

247,686

Dependencies

76,198

Author Associations

28,834

Publication Badges

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