noisySBM
Noisy Stochastic Block Mode: Graph Inference by Multiple Testing
Variational Expectation-Maximization algorithm to fit the noisy stochastic block model to an observed dense graph and to perform a node clustering. Moreover, a graph inference procedure to recover the underlying binary graph. This procedure comes with a control of the false discovery rate. The method is described in the article "Powerful graph inference with false discovery rate control" by T. Rebafka, E. Roquain, F. Villers (2020) <arXiv:1907.10176>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.4 |
rolling linux/jammy R-4.5 | noisySBM_0.1.4.tar.gz |
1.4 MiB |
0.1.4 |
rolling linux/noble R-4.5 | noisySBM_0.1.4.tar.gz |
1.4 MiB |
0.1.4 |
rolling source/ R- | noisySBM_0.1.4.tar.gz |
1.2 MiB |
0.1.4 |
latest linux/jammy R-4.5 | noisySBM_0.1.4.tar.gz |
1.4 MiB |
0.1.4 |
latest linux/noble R-4.5 | noisySBM_0.1.4.tar.gz |
1.4 MiB |
0.1.4 |
latest source/ R- | noisySBM_0.1.4.tar.gz |
1.2 MiB |
0.1.4 |
2026-04-26 source/ R- | noisySBM_0.1.4.tar.gz |
1.2 MiB |
0.1.4 |
2026-04-23 source/ R- | noisySBM_0.1.4.tar.gz |
1.2 MiB |
0.1.4 |
2026-04-09 windows/windows R-4.5 | noisySBM_0.1.4.zip |
1.4 MiB |
0.1.4 |
2025-04-20 source/ R- | noisySBM_0.1.4.tar.gz |
1.2 MiB |