Package: vennLasso 0.2.0

vennLasso: Variable Selection for Heterogeneous Populations

Provides variable selection and estimation routines for models with main effects stratified on multiple binary factors. The 'vennLasso' package is an implementation of the method introduced in Huling et al. (2018) <doi:10.1111/biom.12769>.

Authors:Jared Huling [aut, cre], Muxuan Liang [ctb], Yixuan Qiu [cph], Gael Guennebaud [cph], Ray Gardner [cph], Jitse Niesen [cph]

vennLasso_0.2.0.tar.gz
vennLasso_0.2.0.zip(r-4.7-x86_64)vennLasso_0.2.0.zip(r-4.7-arm64)vennLasso_0.2.0.zip(r-4.6-x86_64)vennLasso_0.2.0.zip(r-4.6-arm64)vennLasso_0.2.0.zip(r-4.5-x86_64)
vennLasso_0.2.0.tgz(r-4.6-x86_64)vennLasso_0.2.0.tgz(r-4.6-arm64)vennLasso_0.2.0.tgz(r-4.5-x86_64)vennLasso_0.2.0.tgz(r-4.5-arm64)
vennLasso_0.2.0.tar.gz(r-4.7-arm64)vennLasso_0.2.0.tar.gz(r-4.7-x86_64)vennLasso_0.2.0.tar.gz(r-4.6-arm64)vennLasso_0.2.0.tar.gz(r-4.6-x86_64)
vennLasso_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
vennLasso/json (API)

# Install 'vennLasso' in R:

install.packages('vennLasso', repos = c('https://jaredhuling.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jaredhuling/vennlasso/issues

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

heterogeneity machine-learning penalized-regression risk-modelling variable-selection cpp

4.94 score 5 stars 35 scripts 102 downloads 9 exports 48 dependencies

Last updated from:86c966c343. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	147
linux-devel-x86_64	OK	186
source / vignettes	OK	233
linux-release-arm64	OK	148
linux-release-x86_64	OK	190
macos-release-arm64	OK	174
macos-release-x86_64	OK	479
macos-oldrel-arm64	OK	172
macos-oldrel-x86_64	OK	383
windows-devel-arm64	OK	282
windows-devel-x86_64	OK	326
windows-release-arm64	OK	263
windows-release-x86_64	OK	240
windows-oldrel-x86_64	OK	291
wasm-release	OK	119

Exports:cv.vennLasso estimate.hier.sparsity.param genHierSparseBeta genHierSparseData oglasso plotCoefs plotSelections plotVenn vennLasso

Dependencies:base64enc bslib cachem cli codetools cpp11 digest evaluate fastmap fontawesome foreach formatR fs futile.logger futile.options glue highr htmltools htmlwidgets igraph iterators jquerylib jsonlite knitr lambda.r lattice lifecycle magrittr MASS Matrix memoise mime pkgconfig R6 rappdirs Rcpp RcppEigen RcppNumerical rlang rmarkdown sass survival tinytex vctrs VennDiagram visNetwork xfun yaml

Using the vennLasso Package

Rendered fromusing_the_vennLasso_package.Rmdusingknitr::rmarkdown

Last update: 2026-11-13
Started: 2017-07-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Cross Validation for the vennLasso	cv.vennLasso
function to estimate the hierarchical sparsity parameter for a desired level of sparsity for simulated hierarchical coefficients	estimate.hier.sparsity.param
function to generate coefficient matrix with hierarchical sparsity	genHierSparseBeta
function to generate data with hierarchical sparsity	genHierSparseData
log likelihood function for fitted vennLasso objects	logLik.vennLasso
Overlapping Group Lasso (OGLasso)	oglasso
Plot method for cv.vennLasso fitted objects	plot.cv.vennLasso plot.vennLasso
plotting function to investigate estimated coefficients	plotCoefs
plotting function to investigate hierarchical structure of selection	plotSelections
plotting function for venn diagrams of overlapping conditions	plotVenn
Prediction for Cross Validation Hierarchical Lasso Object	predict.cv.vennLasso
Prediction for Hierarchical Shared Lasso	predict.vennLasso
Fitting vennLasso models	vennLasso