cv_all

Split Knockoff is a data adaptive variable selection framework for controlling the
(directional) false discovery rate (FDR) in structural sparsity, where variable
selection on linear transformation of parameters is of concern. This proposed scheme
relaxes the linear subspace constraint to its neighborhood, often known as variable
splitting in optimization.
Simulation experiments can be reproduced following the Vignette.
'Split Knockoffs' is first defined in Cao et al. (2021) <doi:10.48550/arXiv.2103.16159>.

Yuxuan Chen

SplitKnockoff

Split Knockoffs for Structural Sparsity

Haoxue Wang

Yang Cao

Xinwei Sun

Yuan Yao

cv_all function

<dl><dt>X</dt>
<dd>the design matrix</dd>
<dt>y</dt>
<dd>the response vector</dd>
<dt>D</dt>
<dd>the linear transform</dd>
<dt>option</dt>
<dd>options for screening</dd></dl>

Arguments

calculate the CV optimal beta — cv_all

<dl>

<dt>X</dt>
<dd>the design matrix</dd>


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


<dt>D</dt>
<dd>the linear transform</dd>


<dt>option</dt>
<dd>options for screening</dd>

</dl>

cv_all: calculate the CV optimal beta

Description

Usage

Value

Arguments