Package: CatReg 2.0.4
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_2.0.4.tar.gz
CatReg_2.0.4.tar.gz(r-4.7-arm64)CatReg_2.0.4.tar.gz(r-4.7-x86_64)CatReg_2.0.4.tar.gz(r-4.6-arm64)CatReg_2.0.4.tar.gz(r-4.6-x86_64)
CatReg_2.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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 from:6689d3362a. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 114 | ||
| linux-devel-x86_64 | OK | 116 | ||
| source / vignettes | OK | 152 | ||
| linux-release-arm64 | OK | 144 | ||
| linux-release-x86_64 | OK | 121 | ||
| wasm-release | OK | 111 |
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 |