On the recordRead 12 Oct 202627 facts
hal9001
On the record
- Available builds
- CRAN lists Windows binaries, macOS binaries for arm64 and x86_64, and a source package.cran.r-project.org · read 12 Oct 2026
- Basis construction
- The package includes routines for constructing sparse matrices of basis functions from observed data.cran.r-project.org · read 12 Oct 2026
- Contributions
- The project welcomes contributions and directs prospective contributors to its contribution guidelines.tlverse.org · read 11 Oct 2026
- Data import formats
- R matrix, numeric vector, or formula interfacetlverse.org · read 24 Sep 2026
- Dependencies
- The package depends on R version 3.1.0 or later and Rcpp, and imports Matrix, stats, utils, methods, assertthat, origami, glmnet, data.table, and stringr.cran.r-project.org · read 12 Oct 2026
- Deployment
- desktoptlverse.org · read 24 Sep 2026
- Development install
- The development version can be installed from the tlverse/hal9001 GitHub repository using remotes::install_github().tlverse.org · read 11 Oct 2026
- Development version
- The development version can be installed from the tlverse/hal9001 GitHub repository using remotes::install_github().tlverse.org · read 12 Oct 2026
- Documentation
- CRAN lists a reference manual and a vignette on fitting the highly adaptive lasso with hal9001.cran.r-project.org · read 12 Oct 2026
- Estimation
- HAL regression can estimate arbitrarily complex functional forms under global smoothness assumptions.tlverse.org · read 11 Oct 2026
- Installation
- The maker recommends installing the package from CRAN with install.packages("hal9001").tlverse.org · read 12 Oct 2026
- Integrations
- CRAN lists glmnet among the package imports and SuperLearner among its suggested packages.cran.r-project.org · read 11 Oct 2026
- Intended use
- The maker describes HAL regression as a way to estimate complex functional forms under global smoothness assumptions, with applications to nuisance parameter estimation.tlverse.org · read 12 Oct 2026
- Lasso fitting
- Its lasso routines use glmnet by default and include a custom implementation tailored to predictors composed of indicator functions.cran.r-project.org · read 12 Oct 2026
- License
- The package is distributed under the GPL-3 license.tlverse.org · read 12 Oct 2026
- Maintainer
- Jeremy Coyle is listed as the package maintainer on CRAN.cran.r-project.org · read 11 Oct 2026
- Method
- It applies L1-regularized lasso regression to indicator functions for covariate supports and their interactions.tlverse.org · read 11 Oct 2026
- Model basis
- It applies L1-regularized lasso regression to indicator-function basis terms for covariates and their interactions.tlverse.org · read 12 Oct 2026
