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) .


Reference manual

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install.packages("kosel")

0.0.1 by Clemence Karmann, 7 years ago


https://arxiv.org/pdf/1907.03153.pdf


Browse source code at https://github.com/cran/kosel


Authors: Clemence Karmann [aut, cre] , Aurelie Gueudin [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports glmnet, ordinalNet

Suggests graphics


See at CRAN