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:
kosel_0.0.1.tar.gz
kosel_0.0.1.tar.gz(r-4.7-any)kosel_0.0.1.tar.gz(r-4.6-any)
kosel_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
kosel/json (API)
| # Install 'kosel' in R: |
| install.packages('kosel', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:887cd64506. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 118 | ||
| source / vignettes | OK | 149 | ||
| linux-release-x86_64 | OK | 93 | ||
| wasm-release | OK | 98 |
Exports:ko.glmko.ordinalko.sel
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixordinalNetRcppRcppEigenshapesurvival
