lingamr
'LiNGAM' Algorithms for Causal Discovery
R implementation of 'LiNGAM' (Linear Non-Gaussian Acyclic Model) algorithms for causal discovery, following Shimizu et al. (2011) <https://www.jmlr.org/papers/v12/shimizu11a.html>. Based on the 'Python' implementation by Ikeuchi et al. (2023) <https://github.com/cdt15/lingam>. The 'VAR-LiNGAM' residual diagnostics are inspired by the 'VARLiNGAM' R code of Moneta et al. <https://sites.google.com/site/dorisentner/publications/VARLiNGAM>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.2 |
rolling linux/jammy R-4.5 | lingamr_0.1.2.tar.gz |
1.4 MiB |
0.1.2 |
rolling linux/noble R-4.5 | lingamr_0.1.2.tar.gz |
1.4 MiB |
0.1.2 |
rolling source/ R- | lingamr_0.1.2.tar.gz |
972.6 KiB |
0.1.2 |
latest linux/jammy R-4.5 | lingamr_0.1.2.tar.gz |
1.4 MiB |
0.1.2 |
latest linux/noble R-4.5 | lingamr_0.1.2.tar.gz |
1.4 MiB |
0.1.2 |
latest source/ R- | lingamr_0.1.2.tar.gz |
972.6 KiB |
0.1.2 |
2026-04-23 source/ R- | lingamr_0.1.2.tar.gz |
0 B |