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Hierarchical Regularized Regression
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.
- Version1.0.0
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- Last release07/16/2024
Documentation
Team
Garrett Weaver
Dixin Shen
Show author detailsRolesAuthorJuan Pablo Lewinger
Show author detailsRolesContributor, Thesis advisor
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- Suggests5 packages
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