Package: BrainCon 0.3.0
BrainCon: Inference the Partial Correlations Based on Time Series Data
A statistical tool to inference the multi-level partial correlations based on multi-subject time series data, especially for brain functional connectivity. It combines both individual and population level inference by using the methods of Qiu and Zhou. (2021)<doi:10.1080/01621459.2021.1917417> and Genovese and Wasserman. (2006)<doi:10.1198/016214506000000339>. It realizes two reliable estimation methods of partial correlation coefficients, using scaled lasso and lasso. It can be used to estimate individual- or population-level partial correlations, identify nonzero ones, and find out unequal partial correlation coefficients between two populations.
Authors:
BrainCon_0.3.0.tar.gz
BrainCon_0.3.0.zip(r-4.5)BrainCon_0.3.0.zip(r-4.4)BrainCon_0.3.0.zip(r-4.3)
BrainCon_0.3.0.tgz(r-4.4-any)BrainCon_0.3.0.tgz(r-4.3-any)
BrainCon_0.3.0.tar.gz(r-4.5-noble)BrainCon_0.3.0.tar.gz(r-4.4-noble)
BrainCon_0.3.0.tgz(r-4.4-emscripten)BrainCon_0.3.0.tgz(r-4.3-emscripten)
BrainCon.pdf |BrainCon.html✨
BrainCon/json (API)
| # Install 'BrainCon' in R: |
| install.packages('BrainCon', repos = c('https://cemrclinicencoding.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 2 years agofrom:4e5832a19b. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | OK | Nov 20 2024 |
| R-4.5-linux | OK | Nov 20 2024 |
| R-4.4-win | OK | Nov 20 2024 |
| R-4.4-mac | OK | Nov 20 2024 |
| R-4.3-win | OK | Nov 20 2024 |
| R-4.3-mac | OK | Nov 20 2024 |
Exports:individual.estindividual.testnormalize.setpopulation.estpopulation.testpopulation.test.MinPvpopulation2sample.testpopulation2sample.test.MinPvQSscaledlasso
Dependencies:codetoolsforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Estimate individual-level partial correlation coefficients | individual.est |
| Identify nonzero individual-level partial correlations | individual.test |
| Simulation time series data for individual | indsim |
| Simulation time series data for population A | popsimA |
| Simulation time series data for population B | popsimB |
| Estimate population-level partial correlation coefficients | population.est |
| The one-sample population inference | population.test |
| The one-sample population inference using Genovese and Wasserman's method | population.test.MinPv |
| Identify differences of partial correlations between two populations | population2sample.test |
| Identify differences of partial correlations between two populations using Genovese and Wasserman's method | population2sample.test.MinPv |
