Package: SplitReg 1.0.2
Anthony Christidis
SplitReg: Split Regularized Regression
Functions for computing split regularized estimators defined in Christidis, Lakshmanan, Smucler and Zamar (2019) <arxiv:1712.03561>. The approach fits linear regression models that split the set of covariates into groups. The optimal split of the variables into groups and the regularized estimation of the regression coefficients are performed by minimizing an objective function that encourages sparsity within each group and diversity among them. The estimated coefficients are then pooled together to form the final fit.
Authors:
SplitReg_1.0.2.tar.gz
SplitReg_1.0.2.tar.gz(r-4.5-noble)SplitReg_1.0.2.tar.gz(r-4.4-noble)
SplitReg_1.0.2.tgz(r-4.4-emscripten)SplitReg_1.0.2.tgz(r-4.3-emscripten)
SplitReg.pdf |SplitReg.html✨
SplitReg/json (API)
NEWS
| # Install 'SplitReg' in R: |
| install.packages('SplitReg', 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 5 years agofrom:9c8392a06f. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 13 2024 |
| R-4.5-linux-x86_64 | OK | Dec 13 2024 |
Exports:cv.SplitReg
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Extract coefficients from a cv.SplitReg object. | coef.cv.SplitReg |
| Split Regularized Regression algorithm with a sparsity and diversity penalty. | cv.SplitReg |
| Make predictions from a cv.SplitReg object. | predict.cv.SplitReg |
