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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.4 |
rolling linux/jammy R-4.5 | SparseICA_0.1.4.tar.gz |
544.8 KiB |
0.1.4 |
rolling linux/noble R-4.5 | SparseICA_0.1.4.tar.gz |
547.0 KiB |
0.1.4 |
rolling source/ R- | SparseICA_0.1.4.tar.gz |
435.8 KiB |
0.1.4 |
latest linux/jammy R-4.5 | SparseICA_0.1.4.tar.gz |
544.8 KiB |
0.1.4 |
latest linux/noble R-4.5 | SparseICA_0.1.4.tar.gz |
547.0 KiB |
0.1.4 |
latest source/ R- | SparseICA_0.1.4.tar.gz |
435.8 KiB |
0.1.4 |
2026-04-26 source/ R- | SparseICA_0.1.4.tar.gz |
435.8 KiB |
0.1.4 |
2026-04-23 source/ R- | SparseICA_0.1.4.tar.gz |
435.8 KiB |
0.1.4 |
2026-04-09 windows/windows R-4.5 | SparseICA_0.1.4.zip |
868.4 KiB |
0.1.4 |
2025-04-20 source/ R- | SparseICA_0.1.4.tar.gz |
435.8 KiB |