lasso_max_lambda

Computes the earliest (largest) lambda's for which predictors enter the
lasso model.

internal

The knockoff filter is 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-X knockoffs for high-dimensional controlled variable selection",
J. R. Statist. Soc. B (2018) 80, 3, pp. 551-577.

Matteo Sesia

knockoff

The Knockoff Filter for Controlled Variable Selection

Rina Foygel Barber

Emmanuel Candes

Lucas Janson

Evan Patterson

lasso_max_lambda function

<dl><dt>X</dt>
<dd>matrix of predictors</dd>
<dt>y</dt>
<dd>response vector</dd>
<dt>method</dt>
<dd>either 'glmnet' or 'lars'</dd></dl>

Arguments

Maximum lambda in lasso model — lasso_max_lambda

<dl>

<dt>X</dt>
<dd>matrix of predictors</dd>


<dt>y</dt>
<dd>response vector</dd>


<dt>method</dt>
<dd>either 'glmnet' or 'lars'</dd>

</dl>

lasso_max_lambda: Maximum lambda in lasso model

Description

Usage

Value

Arguments