R: The Knockoff Filter for Controlled Variable Selection

# The Knockoff Filter for Controlled Variable Selection

## Documentation for package ‘knockoff’ version 0.3.6

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

create.fixed | Fixed-X knockoffs
create.gaussian | Model-X Gaussian knockoffs
create.second_order | Second-order Gaussian knockoffs
create.solve_asdp | Relaxed optimization for fixed-X and Gaussian knockoffs
create.solve_equi | Optimization for equi-correlated fixed-X and Gaussian knockoffs
create.solve_sdp | Optimization for fixed-X and Gaussian knockoffs
knockoff | knockoff: A package for controlled variable selection
knockoff.filter | The Knockoff Filter
knockoff.threshold | Threshold for the knockoff filter
print.knockoff.result | Print results for the knockoff filter
stat.forward_selection | Importance statistics based on forward selection
stat.glmnet_coefdiff | Importance statistics based on a GLM with cross-validation
stat.glmnet_lambdadiff | Importance statistics based on a GLM
stat.glmnet_lambdasmax | GLM statistics for knockoff
stat.lasso_coefdiff | Importance statistics based the lasso with cross-validation
stat.lasso_coefdiff_bin | Importance statistics based on regularized logistic regression with cross-validation
stat.lasso_lambdadiff | Importance statistics based on the lasso
stat.lasso_lambdadiff_bin | Importance statistics based on regularized logistic regression
stat.lasso_lambdasmax | Penalized linear regression statistics for knockoff
stat.lasso_lambdasmax_bin | Penalized logistic regression statistics for knockoff
stat.random_forest | Importance statistics based on random forests
stat.sqrt_lasso | Importance statistics based on the square-root lasso
stat.stability_selection | Importance statistics based on stability selection