Package: uniLasso 2.11
uniLasso: Univariate-Guided Sparse Regression
Fit a univariate-guided sparse regression (lasso), by a two-stage procedure. The first stage fits p separate univariate models to the response. The second stage gives more weight to the more important univariate features, and preserves their signs. Conveniently, it returns an objects that inherits from class 'glmnet', so that all of the methods for 'glmnet' are available. See Chatterjee, Hastie and Tibshirani (2025) <doi:10.1162/99608f92.c79ff6db> for details.
Authors:
uniLasso_2.11.tar.gz
uniLasso_2.11.zip(r-4.7)uniLasso_2.11.zip(r-4.6)uniLasso_2.11.zip(r-4.5)
uniLasso_2.11.tgz(r-4.6-any)uniLasso_2.11.tgz(r-4.5-any)
uniLasso_2.11.tar.gz(r-4.7-any)uniLasso_2.11.tar.gz(r-4.6-any)
uniLasso_2.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
uniLasso/json (API)
| # Install 'uniLasso' in R: |
| install.packages('uniLasso', repos = c('https://trevorhastie.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/trevorhastie/unilasso/issues
Last updated from:0f0a44ab49. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 115 | ||
| source / vignettes | OK | 186 | ||
| linux-release-x86_64 | OK | 120 | ||
| macos-release-arm64 | OK | 93 | ||
| macos-oldrel-arm64 | OK | 111 | ||
| windows-devel | OK | 98 | ||
| windows-release | OK | 179 | ||
| windows-oldrel | OK | 90 | ||
| wasm-release | OK | 101 |
Exports:ci.uniRegcv.uniLassocv.uniRegpolish.uniLassoprint.cv.uniRegsimulate_counterexamplesimulate_Gaussiansimulate_twoclasssimulate_uniLassouniCoefuniInfouniLassouniReg
Dependencies:codetoolsforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute bootstrap confidence intervals for a univariate guided regression model | ci.uniReg uniLasso uniReg |
| Fit a cross-validated univariate guided lasso model. | cv.uniLasso cv.uniReg |
| plot the cross-validation curve produced by cv.uniReg | plot.cv.uniReg |
| Fit a cross-validated univariate guided lasso model, followed by a lasso polish. | polish.uniLasso |
| make predictions from a "cv.uniReg" object. | predict.cv.uniReg |
| print a cross-validated uniReg object | print.cv.uniReg |
| simulate counterexample data | simulate_counterexample |
| simulate Gaussian data | simulate_Gaussian |
| simulate two class data | simulate_twoclass |
| Simulate data for use in uniLasso and uniReg | simulate_uniLasso |
| Compare the nonzero coefficients and univariate counterparts | uniCoef |
| Create the univariate info for use in uniLasso | uniInfo |
