xrnet: 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.

Getting started

Package details

AuthorGarrett Weaver [aut, cre] (<https://orcid.org/0000-0002-9918-8386>), Juan Pablo Lewinger [ctb, ths]
MaintainerGarrett Weaver <gmweaver.usc@gmail.com>
LicenseGPL-2
Version0.1.7
URL https://github.com/USCbiostats/xrnet
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("xrnet")

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xrnet documentation built on March 26, 2020, 9:13 p.m.