Package: CVR 0.1.1
Chongliang Luo
CVR: Canonical Variate Regression
Perform canonical variate regression (CVR) for two sets of covariates and a univariate response, with regularization and weight parameters tuned by cross validation.
Authors:
CVR_0.1.1.tar.gz
CVR_0.1.1.tar.gz(r-4.5-noble)CVR_0.1.1.tar.gz(r-4.4-noble)
CVR_0.1.1.tgz(r-4.4-emscripten)CVR_0.1.1.tgz(r-4.3-emscripten)
CVR.pdf |CVR.html✨
CVR/json (API)
| # Install 'CVR' in R: |
| install.packages('CVR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:2acdcd2056. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 07 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 07 2024 |
Exports:CVRcvrsolverSimulateCVRSparseCCA
Dependencies:PMARcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Canonical Variate Regression | CVR-package |
| Data sets for the alcohol dependence example | alcohol |
| Fit canonical variate regression with tuning parameters selected by cross validation. | CVR |
| Canonical Variate Regression. | cvrsolver |
| Data sets for the mouse body weight example | mouse |
| Plot a CVR object. | plot.CVR |
| Generate simulation data. | SimulateCVR |
| Sparse canonical correlation analysis. | SparseCCA |