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SparseICA (version 0.1.4)

Sparse Independent Component Analysis

Description

Provides an implementation of the Sparse ICA method in Wang et al. (2024) 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.

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Install

install.packages('SparseICA')

Monthly Downloads

179

Version

0.1.4

License

GPL-3

Issues

0

Pull Requests

0

Stars

6

Forks

2

Maintainer

Zihang Wang

Last Published

January 29th, 2025

Functions in SparseICA (0.1.4)

signchange

Change the sign of S and M matrices to positive skewness.
whitener

The function for perform whitening.
soft_thresh_R

Soft-threshold function
givens.rotation

For a given angle theta, returns a d x d Givens rotation matrix
example_sim123

Example sim123 Dataset
est.M.ols

Estimate mixing matrix from estimates of components
group_sparseICA

Perform Group Sparse Independent Component Analysis (Sparse ICA)
gen_groupPC

Generate Group-Level Principal Components (PCs) for fMRI Data
gen.inits

Function for generating random starting points
relax_and_split_ICA

Relax-and-split ICA Function for Sparse ICA wrapper
matchICA

Match ICA results based on L2 distances and Hungarian
BIC_sparseICA

BIC-like Criterion for Tuning Parameter Selection in Sparse ICA
create_group_list

Create a List of fMRI Files for Group ICA Analysis
sparseICA

Sparse Independent Component Analysis (Sparse ICA) Function
theta2W

Convert angle vector into orthodox matrix