CRAN/E | xrnet

xrnet

Hierarchical Regularized Regression

Installation

About

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.

github.com/USCbiostats/xrnet
System requirements C++11

Key Metrics

Version 0.1.7
R ≥ 3.5
Published 2020-03-01 1523 days ago
Needs compilation? yes
License GPL-2
CRAN checks xrnet results

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Maintainer

Maintainer

Garrett Weaver

gmweaver.usc@gmail.com

Authors

Garrett Weaver

aut / cre

Juan Pablo Lewinger

ctb / ths

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

xrnet archive

Depends

R ≥ 3.5

Imports

Rcpp ≥ 0.12.19
foreach
bigmemory
methods

Suggests

knitr
rmarkdown
testthat
Matrix
doParallel

LinkingTo

Rcpp
RcppEigen
BH
bigmemory