soft_thresh_R

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

soft_thresh_R function

<dl><dt>x</dt>
<dd>The input scalar.</dd>
<dt>nu</dt>
<dd>The tuning parameter.</dd>
<dt>lambda</dt>
<dd>The lambda parameter of the Laplace density.</dd></dl>

Arguments

Soft-threshold function — soft_thresh_R

<dl>

<dt>x</dt>
<dd>The input scalar.</dd>


<dt>nu</dt>
<dd>The tuning parameter.</dd>


<dt>lambda</dt>
<dd>The lambda parameter of the Laplace density.</dd>

</dl>

soft_thresh_R: Soft-threshold function

Description

Usage

Arguments