Package: kosel 0.0.1

Clemence Karmann

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>.

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

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kosel.pdf |kosel.html✨
kosel/json (API)

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3 exports 0.00 score 11 dependencies 145 downloads

Last updated 5 years agofrom:887cd64506. Checks:OK: 2. Indexed: yes.

Exports:ko.glmko.ordinalko.sel

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixordinalNetRcppRcppEigenshapesurvival