Package: cvLM 1.0.4
cvLM: Cross-Validation for Linear & Ridge Regression Models
Efficient implementations of cross-validation techniques for linear and ridge regression models, leveraging 'C++' code with 'Rcpp', 'RcppParallel', and 'Eigen' libraries. It supports leave-one-out, generalized, and K-fold cross-validation methods, utilizing 'Eigen' matrices for high performance. Methodology references: Hastie, Tibshirani, and Friedman (2009) <doi:10.1007/978-0-387-84858-7>.
Authors:
cvLM_1.0.4.tar.gz
cvLM_1.0.4.zip(r-4.5)cvLM_1.0.4.zip(r-4.4)cvLM_1.0.4.zip(r-4.3)
cvLM_1.0.4.tgz(r-4.4-x86_64)cvLM_1.0.4.tgz(r-4.4-arm64)cvLM_1.0.4.tgz(r-4.3-x86_64)cvLM_1.0.4.tgz(r-4.3-arm64)
cvLM_1.0.4.tar.gz(r-4.5-noble)cvLM_1.0.4.tar.gz(r-4.4-noble)
cvLM_1.0.4.tgz(r-4.4-emscripten)cvLM_1.0.4.tgz(r-4.3-emscripten)
cvLM.pdf |cvLM.html✨
cvLM/json (API)
| # Install 'cvLM' in R: |
| install.packages('cvLM', repos = c('https://phipnye.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 months agofrom:b372e0a408. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 01 2024 |
| R-4.5-win-x86_64 | NOTE | Sep 01 2024 |
| R-4.5-linux-x86_64 | NOTE | Sep 01 2024 |
| R-4.4-win-x86_64 | NOTE | Sep 01 2024 |
| R-4.4-mac-x86_64 | NOTE | Sep 01 2024 |
| R-4.4-mac-aarch64 | NOTE | Sep 01 2024 |
| R-4.3-win-x86_64 | NOTE | Sep 01 2024 |
| R-4.3-mac-x86_64 | NOTE | Sep 01 2024 |
| R-4.3-mac-aarch64 | NOTE | Sep 01 2024 |
Exports:cvLMgrid.searchreg.table
Dependencies:RcppRcppEigenRcppParallel
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Cross-validation for linear and ridge regression models | cvLM-package cvLM cvLM.formula cvLM.glm cvLM.lm |
| Grid Search for Optimal Lambda in Ridge Regression | grid.search |
| Create Regression Tables in LaTeX or HTML | reg.table |
