normc

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

normc function

<dl><dt>X</dt>
<dd>the input martix</dd></dl>

Arguments

default normalization function for matrix — normc

<dl>

<dt>X</dt>
<dd>the input martix</dd>

</dl>

default normalization function for matrix

normc: default normalization function for matrix

Description

Usage

Value

Arguments

Examples