USCbiostats/hierr: Hierarchical Regularized Regression

Fits hierarchical regularized regression models to incoporate potentially informative external data. 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 M. Weaver
MaintainerGarrett M. Weaver <[email protected]>
LicenseGPL-2 | file LICENSE
Version0.1.2
URL https://github.com/USCbiostats/xrnet
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("USCbiostats/hierr")
USCbiostats/hierr documentation built on Nov. 12, 2019, 1:49 p.m.