matchICA

Match ICA results based on L2 distances and Hungarian

Provides an implementation of the Sparse ICA method in Wang et al. (2024) <doi:10.1080/01621459.2024.2370593> for estimating sparse independent source components of cortical surface functional MRI data, by addressing a non-smooth, non-convex optimization problem through the relax-and-split framework. This method effectively balances statistical independence and sparsity while maintaining computational efficiency.

Zihang Wang

SparseICA

Sparse Independent Component Analysis

Irina Gaynanova

Aleksandr Aravkin

Benjamin Risk

matchICA function

<dl><dt>S</dt>
<dd>loading variable matrix</dd>
<dt>template</dt>
<dd>template for match</dd>
<dt>M</dt>
<dd>subject score matrix</dd></dl>

Arguments

Match ICA results based on L2 distances and Hungarian — matchICA

<dl>

<dt>S</dt>
<dd>loading variable matrix</dd>


<dt>template</dt>
<dd>template for match</dd>


<dt>M</dt>
<dd>subject score matrix</dd>

</dl>

matchICA: Match ICA results based on L2 distances and Hungarian

Description

Usage

Value

Arguments