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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.1 |
rolling linux/jammy R-4.5 | kosel_0.0.1.tar.gz |
33.9 KiB |
0.0.1 |
rolling linux/noble R-4.5 | kosel_0.0.1.tar.gz |
33.9 KiB |
0.0.1 |
rolling source/ R- | kosel_0.0.1.tar.gz |
7.0 KiB |
0.0.1 |
latest linux/jammy R-4.5 | kosel_0.0.1.tar.gz |
33.9 KiB |
0.0.1 |
latest linux/noble R-4.5 | kosel_0.0.1.tar.gz |
33.9 KiB |
0.0.1 |
latest source/ R- | kosel_0.0.1.tar.gz |
7.0 KiB |
0.0.1 |
2026-04-26 source/ R- | kosel_0.0.1.tar.gz |
7.0 KiB |
0.0.1 |
2026-04-23 source/ R- | kosel_0.0.1.tar.gz |
7.0 KiB |
0.0.1 |
2026-04-09 windows/windows R-4.5 | kosel_0.0.1.zip |
36.5 KiB |
0.0.1 |
2025-04-20 source/ R- | kosel_0.0.1.tar.gz |
7.0 KiB |