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kosel  

Variable Selection by Revisited Knockoffs Procedures
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("kosel", "0.0.1")



Attach the package and use:
library("kosel")
Maintained by
Clemence Karmann
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-07-18
Latest Update: 2019-07-18
Description:
Performs variable selection for many types of L1-regularised regressions using the revisited knockoffs procedure. This procedure uses a matrix of knockoffs of the covariates independent from the response variable Y. The idea is to determine if a covariate belongs to the model depending on whether it enters the model before or after its knockoff. The procedure suits for a wide range of regressions with various types of response variables. Regression models available are exported from the R packages 'glmnet' and 'ordinalNet'. Based on the paper linked to via the URL below: Gegout A., Gueudin A., Karmann C. (2019) .
How to cite:
Clemence Karmann (2019). kosel: Variable Selection by Revisited Knockoffs Procedures. R package version 0.0.1, https://cran.r-project.org/web/packages/kosel. Accessed 25 Oct. 2026.
Previous versions and publish date:
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Complete documentation for kosel
Functions, R codes and Examples using the kosel R package
Some associated functions: ko.glm . ko.ordinal . ko.sel . 
Some associated R codes: cusum.R . ko.glm.R . ko.ordinal.R . ko.sel.R . rupt.detection.R .  Full kosel package functions and examples
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