Hierarchical Regularized Regression R package xrnet version 1.0.1 Fits hierarchical regularized regression models to incorporate potentially informative external data, Weaver and Lewinger (2019) <doi:10.21105/joss.01761>. Utilizes coordinate descent to efficiently fit regularized regression models both with and without external information with the most common penalties used in practice (i.e. ridge, lasso, elastic net). Support for standard R matrices, sparse matrices and big.matrix objects. Software Depends: R (>= 4.0) Imports: Rcpp (>= 0.12.19), foreach, bigmemory, methods LinkingTo: Rcpp, RcppEigen, BH, bigmemory Suggests: knitr, rmarkdown, testthat, Matrix, doParallel Garrett Weaver <gweaverdev@icloud.com> Comprehensive R Archive Network (CRAN) Garrett Weaver [aut, cre] (ORCID: <https://orcid.org/0000-0002-9918-8386>), Dixin Shen [aut], Juan Pablo Lewinger [ctb, ths] GPL-2 2025-12-18 application/tgz https://CRAN.R-project.org/package=xrnet doi:10.32614/CRAN.package.xrnet