kosel: Variable Selection by Revisited Knockoffs Procedures

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) <arXiv:1907.03153>.

Getting started

Package details

AuthorClemence Karmann [aut, cre], Aurelie Gueudin [aut]
MaintainerClemence Karmann <[email protected]>
LicenseGPL-3
Version0.0.1
URL https://arxiv.org/pdf/1907.03153.pdf
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("kosel")

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kosel documentation built on July 18, 2019, 5:04 p.m.