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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