sigPCA
Statistical Significance Testing for Principal Components
Identifies principal components whose eigenvalues exceed those expected under noise. Implements analytical thresholds derived from the Marchenko-Pastur distribution (Marchenko and Pastur, 1967) <doi:10.1070/SM1967v001n04ABEH001994> and empirical permutation tests, and provides functions for visualizing observed and null eigenvalue spectra.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | sigPCA_0.1.0.tar.gz |
240.6 KiB |
0.1.0 |
rolling linux/noble R-4.5 | sigPCA_0.1.0.tar.gz |
240.4 KiB |
0.1.0 |
rolling source/ R- | sigPCA_0.1.0.tar.gz |
221.2 KiB |
0.1.0 |
latest linux/jammy R-4.5 | sigPCA_0.1.0.tar.gz |
240.6 KiB |
0.1.0 |
latest linux/noble R-4.5 | sigPCA_0.1.0.tar.gz |
240.4 KiB |
0.1.0 |
latest source/ R- | sigPCA_0.1.0.tar.gz |
221.2 KiB |
0.1.0 |
2026-04-23 source/ R- | sigPCA_0.1.0.tar.gz |
0 B |