stability_selection_importance

<p>Perform variable selection with stability selection</p>

internal

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, <arXiv:1610.02351>.

Matteo Sesia

MFKnockoffs

Model-Free Knockoff Filter for Controlled Variable Selection

Rina Foygel Barber

Emmanuel Candes

Lucas Janson

Evan Patterson

stability_selection_importance function

Stability selection — stability_selection_importance

Stability selection

stability_selection_importance: Stability selection

Description

Usage

Arguments

Value