normalblockr
Gaussian Graphical Models with Latent Clustering Structure
Implements the Normal-Block model, a Gaussian graphical model with a latent clustering structure for the multivariate analysis of continuous data. The model clusters variables and, building on the graphical lasso, infers a network of statistical dependencies between clusters rather than between individual variables, for known or unknown clusterings, with an optional zero-inflation extension for data with an excess of exact zeros. See Tous & Chiquet (2026) <doi:10.1016/j.csda.2026.108347> for the model itself and its variational expectation-maximization estimation procedure.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.1 |
rolling linux/jammy R-4.5 | normalblockr_0.2.1.tar.gz |
1.9 MiB |
0.2.1 |
rolling linux/noble R-4.5 | normalblockr_0.2.1.tar.gz |
1.9 MiB |
0.2.1 |
rolling source/ R- | normalblockr_0.2.1.tar.gz |
1.3 MiB |
0.2.1 |
latest linux/jammy R-4.5 | normalblockr_0.2.1.tar.gz |
1.9 MiB |
0.2.1 |
latest linux/noble R-4.5 | normalblockr_0.2.1.tar.gz |
1.9 MiB |
0.2.1 |
latest source/ R- | normalblockr_0.2.1.tar.gz |
1.3 MiB |
0.2.1 |
2026-04-23 source/ R- | normalblockr_0.2.1.tar.gz |
0 B |