Package: sparselink 1.0.0
sparselink: Sparse Regression for Related Problems
Estimates sparse regression models (i.e., with few non-zero coefficients) in high-dimensional multi-task learning and transfer learning settings, as proposed by Rauschenberger et al. (2025) <doi:10.1093/bioinformatics/btaf406>.
Authors:
sparselink_1.0.0.tar.gz
sparselink_1.0.0.zip(r-4.7)sparselink_1.0.0.zip(r-4.6)sparselink_1.0.0.zip(r-4.5)
sparselink_1.0.0.tgz(r-4.6-any)sparselink_1.0.0.tgz(r-4.5-any)
sparselink_1.0.0.tar.gz(r-4.7-any)sparselink_1.0.0.tar.gz(r-4.6-any)
sparselink_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sparselink/json (API)
NEWS
| # Install 'sparselink' in R: |
| install.packages('sparselink', repos = c('https://rauschenberger.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rauschenberger/sparselink/issues
Pkgdown/docs site:https://rauschenberger.github.io
Last updated from:e53222f2c9. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 181 | ||
| source / vignettes | OK | 222 | ||
| linux-release-x86_64 | OK | 170 | ||
| macos-release-arm64 | OK | 148 | ||
| macos-oldrel-arm64 | OK | 98 | ||
| windows-devel | OK | 134 | ||
| windows-release | OK | 126 | ||
| windows-oldrel | OK | 182 | ||
| wasm-release | OK | 127 |
Exports:calc_metricconstruct_penfacsconstruct_weightscount_matrixcount_vectorcv_multiplecv_transferfuse_dataget_infolink_functionlogitmake_folds_multimake_folds_transmean_functionplot_changeplot_weightsigmoidsim_data_multisim_data_transsparselinktraintestwrap_commonwrap_emptywrap_glmtranswrap_mgaussianwrap_separatewrap_splswrap_xrnet
Dependencies:BHbigmemorybigmemory.sricodetoolsforeachglmnetiteratorslatticeMASSMatrixmvtnormnnetplspROCRcppRcppEigenshapesplssurvivaluuidxrnet
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sparse regression for related problems | sparselink-package |
| Regression Coefficients | coef.sparselink |
| Out-of-sample Predictions | predict.sparselink |
| Sparse regression for related problems | sparselink |
