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MFKnockoffs (version 0.9.1)

Model-Free Knockoff Filter for Controlled Variable Selection

Description

Model-free knockoffs are a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for Gold: Model-free Knockoffs for High-dimensional Controlled Variable Selection", 2016, .

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Version

Install

install.packages('MFKnockoffs')

Monthly Downloads

1

Version

0.9.1

License

GPL-3

Maintainer

Matteo Sesia

Last Published

September 29th, 2017

Functions in MFKnockoffs (0.9.1)

MFKnockoffs.filter

Model-Free Knockoff Filter
MFKnockoffs.knocks.solve_asdp

Optimization for SDP knockoffs
MFKnockoffs.stat.random_forest

Random forest statistics for MFKnockoffs
MFKnockoffs.stat.sqrt_lasso

SQRT-lasso statistics for Knockoff
MFKnockoffs.knocks.vectorize_matrix

Vectorize a matrix into the SCS format
MFKnockoffs.knocks.solve_equi

Optimization for equi-correlated knockoffs
MFKnockoffs.knocks.solve_sdp

Optimization for SDP knockoffs
MFKnockoffs.stat.lasso_lambda_difference

Penalized linear regression statistics for MFKnockoffs
MFKnockoffs.stat.lasso_lambda_difference_bin

Penalized logistic regression statistics for MFKnockoffs
sqrt_lasso_coeffs

SQRT lasso
stability_selection_importance

Stability selection
MFKnockoffs

Model-free controlled variable selection
MFKnockoffs.create.approximate_gaussian

Sample approximate second-order multivariate Gaussian knockoff variables
MFKnockoffs.stat.glmnet_lambda_signed_max

GLM statistics for MFKnockoffs
verify_stat_depends

Verify dependencies for chosen statistics
MFKnockoffs.stat.forward_selection

Forward selection statistics for MFKnockoffs
MFKnockoffs.stat.glmnet_lambda_difference

GLM statistics for MFKnockoffs
MFKnockoffs.stat.lasso_lambda_signed_max

Penalized linear regression statistics for MFKnockoffs
MFKnockoffs.stat.lasso_lambda_signed_max_bin

Penalized logistic regression statistics for MFKnockoffs
MFKnockoffs.stat.lasso_coef_difference

Cross-validated penalized linear regression statistics for MFKnockoffs
MFKnockoffs.stat.stability_selection

Stability selection statistics for MFKnockoffs
MFKnockoffs.threshold

Threshold for the knockoff filter
MFKnockoffs.create.fixed

Create fixed-design knockoff variables
MFKnockoffs.create.gaussian

Sample multivariate Gaussian knockoff variables
divide_sdp

Approximate a covariance matrix by a block diagonal matrix with blocks of approximately equal size using Ward's method for hierarchical clustering
fs

Forward selection
MFKnockoffs.stat.lasso_coef_difference_bin

Cross-validated penalized logistic regression statistics for MFKnockoffs
MFKnockoffs.stat.glmnet_coef_difference

Cross-validated GLM statistics for MFKnockoffs
lasso_max_lambda_lars

Maximum lambda in lasso model
print.MFKnockoffs.result

Print results for the knockoff filter