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kko  

Kernel Knockoffs Selection for Nonparametric Additive Models
View on CRAN: Click here


Download and install kko package within the R console
Install from CRAN:
install.packages("kko")

Install from Github:
library("remotes")
install_github("cran/kko")

Install by package version:
library("remotes")
install_version("kko", "1.0.1")



Attach the package and use:
library("kko")
Maintained by
Xiang Lyu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-01
Latest Update: 2022-02-01
Description:
A variable selection procedure, dubbed KKO, for nonparametric additive model with finite-sample false discovery rate control guarantee. The method integrates three key components: knockoffs, subsampling for stability, and random feature mapping for nonparametric function approximation. For more information, see the accompanying paper: Dai, X., Lyu, X., & Li, L. (2021).
How to cite:
Xiang Lyu (2022). kko: Kernel Knockoffs Selection for Nonparametric Additive Models. R package version 1.0.1, https://cran.r-project.org/web/packages/kko
Previous versions and publish date:
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Other R packages that kko depends, imports, suggests or enhances
Functions, R codes and Examples using the kko R package
Some associated functions: KO_evaluation . generate_data . kko . rk_fit . rk_subsample . rk_tune . 
Some associated R codes: KO_evaluation.R . generate_data.R . kko.R . rk_fit.R . rk_subsample.R . rk_tune.R .  Full kko package functions and examples
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