Package: noisysbmGGM 0.1.2.3
noisysbmGGM: Noisy Stochastic Block Model for GGM Inference
Greedy Bayesian algorithm to fit the noisy stochastic block model to an observed sparse graph. Moreover, a graph inference procedure to recover Gaussian Graphical Model (GGM) from real data. This procedure comes with a control of the false discovery rate. The method is described in the article "Enhancing the Power of Gaussian Graphical Model Inference by Modeling the Graph Structure" by Kilian, Rebafka, and Villers (2024) <arxiv:2402.19021>.
Authors:
noisysbmGGM_0.1.2.3.tar.gz
noisysbmGGM_0.1.2.3.zip(r-4.5)noisysbmGGM_0.1.2.3.zip(r-4.4)noisysbmGGM_0.1.2.3.zip(r-4.3)
noisysbmGGM_0.1.2.3.tgz(r-4.4-x86_64)noisysbmGGM_0.1.2.3.tgz(r-4.4-arm64)noisysbmGGM_0.1.2.3.tgz(r-4.3-x86_64)noisysbmGGM_0.1.2.3.tgz(r-4.3-arm64)
noisysbmGGM_0.1.2.3.tar.gz(r-4.5-noble)noisysbmGGM_0.1.2.3.tar.gz(r-4.4-noble)
noisysbmGGM.pdf |noisysbmGGM.html✨
noisysbmGGM/json (API)
| # Install 'noisysbmGGM' in R: |
| install.packages('noisysbmGGM', repos = c('https://valentinkil.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:fff021ac7b. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 02 2024 |
| R-4.5-win-x86_64 | OK | Nov 02 2024 |
| R-4.5-linux-x86_64 | OK | Nov 02 2024 |
| R-4.4-win-x86_64 | OK | Nov 02 2024 |
| R-4.4-mac-x86_64 | OK | Nov 02 2024 |
| R-4.4-mac-aarch64 | OK | Nov 02 2024 |
| R-4.3-win-x86_64 | OK | Nov 02 2024 |
| R-4.3-mac-x86_64 | OK | Nov 02 2024 |
| R-4.3-mac-aarch64 | OK | Nov 02 2024 |
Exports:ARImain_noisySBMmain_noisySBM_GGMmatrixToVecplotGraphsrnsbmvecToMatrix
Dependencies:clicpp11glassogluehugeigraphlatticelifecyclemagrittrMASSMatrixpkgconfigplyrppcorRColorBrewerRcppRcppArmadilloRcppEigenreshaperlangSILGGMvctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Evalute the adjusted Rand index | ARI |
| GGM for test | GGMtest |
| Graph Inference from Noisy Data by Multiple Testing | main_noisySBM |
| GGM Inference from Noisy Data by Multiple Testing using SILGGM and Drton test statistics | main_noisySBM_GGM |
| matrixToVec | matrixToVec |
| NoisySBM for test | NSBMtest |
| plot the data matrix, the inferred graph and/or the true binary graph | plotGraphs |
| return a random NSBM | rnsbm |
| vecToMatrix | vecToMatrix |
