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rqPen
Penalized Quantile Regression
View on CRAN: Click
here
Download and install rqPen package within the R console
Install from CRAN:
install.packages("rqPen")
Install from Github:
library("remotes")
install_github("cran/rqPen") Install by package version:
library("remotes")
install_version("rqPen", "4.2") Attach the package and use:
library("rqPen")
Maintained by
Ben Sherwood
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-10-29
Latest Update: 2025-02-13
Description:
Performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to a work in progress vignette.
How to cite:
Ben Sherwood (2014). rqPen: Penalized Quantile Regression. R package version 4.2, https://cran.r-project.org/web/packages/rqPen. Accessed 05 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:53), 1.0 (2014-10-29 07:44), 1.1 (2015-03-15 17:47), 1.2 (2015-10-22 22:14), 1.3 (2016-02-08 23:32), 1.4 (2016-04-21 08:20), 1.5.1 (2016-11-05 00:45), 1.5 (2016-10-24 17:20), 2.0 (2017-05-16 23:51), 2.1 (2019-05-01 23:20), 2.2.1 (2020-01-28 18:10), 2.2.2 (2020-04-09 19:10), 2.2 (2019-12-10 22:10), 2.3 (2022-03-22 13:50), 3.0.1 (2023-01-31 21:40), 3.0 (2022-08-09 20:10), 3.1.1 (2023-03-04 00:00), 3.1.2 (2023-03-29 00:10), 3.1.3 (2023-04-11 19:10), 3.1 (2023-02-21 00:10), 3.2.1 (2023-08-24 20:00), 3.2.2 (2024-03-14 21:50), 3.2 (2023-07-17 17:10), 4.0 (2024-04-18 20:12), 4.1.1 (2024-06-04 15:30), 4.1.2 (2024-10-29 17:10), 4.1.3 (2025-02-13 11:40), 4.1.4 (2025-12-18 07:10), 4.1 (2024-05-07 23:00)
Other packages that cited rqPen R package
View rqPen citation profile
Other R packages that rqPen depends,
imports, suggests or enhances
Complete documentation for rqPen
Functions, R codes and Examples using
the rqPen R package
Some associated functions: QICD.nonpen . QICD . beta_plots . bytau.plot . bytau.plot.rq.pen.seq.cv . bytau.plot.rq.pen.seq . coef.cv.rq.group.pen . coef.cv.rq.pen . coef.rq.pen.seq.cv . coef.rq.pen.seq . cv.rq.group.pen . cv.rq.pen . cv_plots . plot.cv.rq.group.pen . plot.rq.pen.seq.cv . plot.rq.pen.seq . predict.cv.rq.pen . predict.qic.select . predict.rq.pen . predict.rq.pen.seq.cv . predict.rq.pen.seq . print.cv.rq.pen . print.qic.select . print.rq.pen . print.rq.pen.seq.cv . print.rq.pen.seq . qic . qic.select . qic.select.rq.pen.seq.cv . qic.select.rq.pen.seq . rq.group.fit . rq.group.pen.cv . rq.group.pen . rq.lasso.fit . rq.nc.fit . rq.pen.cv . rq.pen . rqPen .
Some associated R codes: QICD_functions.R . mainFunctions.R . rqPen.R . workHorse.R . Full rqPen package functions and examples
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