Package: MNS 1.0
MNS: Mixed Neighbourhood Selection
An implementation of the mixed neighbourhood selection (MNS) algorithm. The MNS algorithm can be used to estimate multiple related precision matrices. In particular, the motivation behind this work was driven by the need to understand functional connectivity networks across multiple subjects. This package also contains an implementation of a novel algorithm through which to simulate multiple related precision matrices which exhibit properties frequently reported in neuroimaging analysis.
Authors:
MNS_1.0.tar.gz
MNS_1.0.zip(r-4.5)MNS_1.0.zip(r-4.4)MNS_1.0.zip(r-4.3)
MNS_1.0.tgz(r-4.4-any)MNS_1.0.tgz(r-4.3-any)
MNS_1.0.tar.gz(r-4.5-noble)MNS_1.0.tar.gz(r-4.4-noble)
MNS_1.0.tgz(r-4.4-emscripten)MNS_1.0.tgz(r-4.3-emscripten)
MNS.pdf |MNS.html✨
MNS/json (API)
# Install 'MNS' in R: |
install.packages('MNS', repos = c('https://piomonti.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 years agofrom:8a46c1f5df. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 02 2024 |
R-4.5-win | OK | Nov 02 2024 |
R-4.5-linux | OK | Nov 02 2024 |
R-4.4-win | OK | Nov 02 2024 |
R-4.4-mac | OK | Nov 02 2024 |
R-4.3-win | OK | Nov 02 2024 |
R-4.3-mac | OK | Nov 02 2024 |
Exports:cv.MNSgen.NetworkMNS
Dependencies:clicodetoolscpp11doParallelforeachglmnetglueigraphiteratorslatticelifecyclemagrittrMASSMatrixmvtnormpkgconfigRcppRcppEigenrlangshapesurvivalvctrs
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Mixed Neighbourhood Selection package | MNS-package |
Select regularization parameters via cross-validation | cv.MNS |
Simulate random networks for a population of subjects | gen.Network |
Mixed Neighbourhood Selection | MNS |
Plotting function for MNS objects | plot.MNS |