permmatRank_joint

Permutation test to get joint components ranks

Implementation of SING algorithm to extract joint and individual non-Gaussian components from two datasets. SING uses an objective function that maximizes the skewness and kurtosis of latent components with a penalty to enhance the similarity between subject scores. Unlike other existing methods, SING does not use PCA for dimension reduction, but rather uses non-Gaussianity, which can improve feature extraction. Benjamin B.Risk, Irina Gaynanova (2021) <doi:10.1214/21-AOAS1466>.

Liangkang Wang

singR

Simultaneous Non-Gaussian Component Analysis

Irina Gaynanova

Benjamin Risk

permmatRank_joint function

<dl><dt>matchedResults</dt>
<dd>results generated by angleMatchICA</dd>
<dt>nperms</dt>
<dd>the number of permutation</dd></dl>

Arguments

Permutation test to get joint components ranks — permmatRank_joint

<dl>

<dt>matchedResults</dt>
<dd>results generated by angleMatchICA</dd>


<dt>nperms</dt>
<dd>the number of permutation</dd>

</dl>

permmatRank_joint: Permutation test to get joint components ranks

Description

Usage

Value

Arguments