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qut  

Quantile Universal Threshold
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("qut", "2.2")



Attach the package and use:
library("qut")
Maintained by
Jairo Diaz-Rodriguez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-09-20
Latest Update:
Description:
Thresholding based tests for null hypothesis of the form A beta =c, and the Quantile Universal Threshold (QUT) for lasso regularization of Generalized Linear Models (GLM) and square-root lasso to obtain a sparse model with a good compromise between high true positive rate and low false discovery rate. Giacobino et al. (2017) . Sardy et al. (2017) .
How to cite:
Jairo Diaz-Rodriguez (2015). qut: Quantile Universal Threshold. R package version 2.2, https://cran.r-project.org/web/packages/qut. Accessed 08 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:46), 1.0.1 (2015-11-23 12:20), 1.0 (2015-09-20 15:41), 1.1 (2016-09-09 12:25), 1.2 (2017-03-10 11:49), 2.0 (2018-01-29 11:41), 2.1 (2018-05-22 18:49), 2.2 (2021-01-19 11:00)
Other packages that cited qut R package
View qut citation profile
Other R packages that qut depends, imports, suggests or enhances
Functions, R codes and Examples using the qut R package
Some associated functions: affinelassotest . chemometrics . internetAd . lambdaqut . predict.qut . processX . qut-package . qut . riboflavin . sigmaqut . sigmarcv . ztf . 
Some associated R codes: affinelassotest.R . coef.qut.R . lambdaqut.R . predict.qut.R . processX.R . qut.R . sigmaqut.R . sigmarcv.R . ztf.R .  Full qut package functions and examples
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