SparseICA: Sparse Independent Component Analysis
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.
| Version: |
0.1.4 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
Rcpp (≥ 1.0.13), MASS (≥ 7.3-58), irlba (≥ 2.3.5), clue (≥
0.3), ciftiTools (≥ 0.16), parallel (≥ 4.1) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Published: |
2025-01-29 |
| DOI: |
10.32614/CRAN.package.SparseICA |
| Author: |
Zihang Wang  [aut,
cre],
Irina Gaynanova
[aut],
Aleksandr Aravkin
[aut],
Benjamin Risk
[aut] |
| Maintainer: |
Zihang Wang <zhwang0378 at gmail.com> |
| BugReports: |
https://github.com/thebrisklab/SparseICA/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/thebrisklab/SparseICA |
| NeedsCompilation: |
yes |
| Citation: |
SparseICA citation info |
| CRAN checks: |
SparseICA results |
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