Package: CatReg 2.0.3
Daniel Grose
CatReg: Solution Paths for Linear and Logistic Regression Models with Categorical Predictors, with SCOPE Penalty
Computes solutions for linear and logistic regression models with potentially high-dimensional categorical predictors. This is done by applying a nonconvex penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The scaling of the solution paths is selected automatically. Includes functionality for selecting tuning parameter lambda by k-fold cross-validation and early termination based on information criteria. Solutions are computed by cyclical block-coordinate descent, iterating an innovative dynamic programming algorithm to compute exact solutions for each block.
Authors:
CatReg_2.0.3.tar.gz
CatReg_2.0.3.tar.gz(r-4.5-noble)CatReg_2.0.3.tar.gz(r-4.4-noble)
CatReg_2.0.3.tgz(r-4.4-emscripten)CatReg_2.0.3.tgz(r-4.3-emscripten)
CatReg.pdf |CatReg.html✨
CatReg/json (API)
| # Install 'CatReg' in R: |
| install.packages('CatReg', repos = c('https://cran.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 3 years agofrom:b88c4bf4b8. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 27 2024 |
Exports:CorrelatedDesignMatrixscopescope.logisticUniformDesignMatrix
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Create a design matrix of categorical variables with correlated columns. | CorrelatedDesignMatrix |
| Computes SCOPE predictions | predict.scope |
| Computes SCOPE logistic predictions | predict.scope.logistic |
| Compute solution for SCOPE linear models. | scope |
| Computes solution for SCOPE logistic models | scope.logistic |
| Create a design matrix of categorical variables. | UniformDesignMatrix |