Package: shock 1.0
shock: Slope Heuristic for Block-Diagonal Covariance Selection in High Dimensional Gaussian Graphical Models
Block-diagonal covariance selection for high dimensional Gaussian graphical models. The selection procedure is based on the slope heuristics.
Authors:
shock_1.0.tar.gz
shock_1.0.zip(r-4.5)shock_1.0.zip(r-4.4)shock_1.0.zip(r-4.3)
shock_1.0.tgz(r-4.4-any)shock_1.0.tgz(r-4.3-any)
shock_1.0.tar.gz(r-4.5-noble)shock_1.0.tar.gz(r-4.4-noble)
shock_1.0.tgz(r-4.4-emscripten)shock_1.0.tgz(r-4.3-emscripten)
shock.pdf |shock.html✨
shock/json (API)
| # Install 'shock' in R: |
| install.packages('shock', repos = c('https://melinagall.r-universe.dev', 'https://cloud.r-project.org')) |
- dataTest - Simulated data to test the R package
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 years agofrom:c5ae1b3b52. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 03 2024 |
| R-4.5-win | OK | Nov 03 2024 |
| R-4.5-linux | OK | Nov 03 2024 |
| R-4.4-win | OK | Nov 03 2024 |
| R-4.4-mac | OK | Nov 03 2024 |
| R-4.3-win | OK | Nov 03 2024 |
| R-4.3-mac | OK | Nov 03 2024 |
Exports:computeLoglikeFromPartitionnetworkInferenceGlassoBICshockSelectsimulateBlockDiagNetworkthresholdAbsSPath
Dependencies:capusheclicpp11GGMselectglassogluegtoolsigraphlarslatticelifecyclemagrittrMASSMatrixmvtnormpkgconfigrlangvctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Slope Heuristic for Block-Diagonal Covariance Selection in High Dimensional Gaussian Graphical Models | shock-package shock |
| Compute the log-likelihood of the model | computeLoglikeFromPartition |
| Simulated data to test the R package | dataTest |
| Network inference using the glasso algorithm | networkInferenceGlassoBIC |
| Shock selection | shockSelect |
| Simulate a modular network | simulateBlockDiagNetwork |
| Detect partitions of variables into blocks. | thresholdAbsSPath |
