Package: xrnet 1.0.1

Garrett Weaver

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.

Authors:Garrett Weaver [aut, cre], Dixin Shen [aut], Juan Pablo Lewinger [ctb, ths]

xrnet_1.0.1.tar.gz
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xrnet_1.0.1.tar.gz(r-4.7-arm64)xrnet_1.0.1.tar.gz(r-4.7-x86_64)xrnet_1.0.1.tar.gz(r-4.6-arm64)xrnet_1.0.1.tar.gz(r-4.6-x86_64)
xrnet_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
xrnet/json (API)
NEWS

# Install 'xrnet' in R:

install.packages('xrnet', repos = c('https://uscbiostats.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/uscbiostats/xrnet/issues

Pkgdown/docs site:https://uscbiostats.github.io

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

ext_linear - Simulated external data
x_linear - Simulated example data for hierarchical regularized linear regression
y_linear - Simulated outcome data

On CRAN:

cpp

4.65 score 10 stars 1 packages 10 scripts 197 downloads 7 exports 9 dependencies

Last updated from:e171fe7424. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	242
linux-devel-x86_64	OK	183
source / vignettes	OK	205
linux-release-arm64	OK	168
linux-release-x86_64	OK	172
macos-release-arm64	OK	142
macos-release-x86_64	OK	320
macos-oldrel-arm64	OK	140
macos-oldrel-x86_64	OK	342
windows-devel	OK	228
windows-release	OK	172
windows-oldrel	OK	111
wasm-release	OK	138

Exports:define_enet define_lasso define_penalty define_ridge tune_xrnet xrnet xrnet_control

Dependencies:BH bigmemory bigmemory.sri codetools foreach iterators Rcpp RcppEigen uuid

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Get coefficient estimates from "tune_xrnet" model object.	coef.tune_xrnet
Get coefficient estimates from "xrnet" model object.	coef.xrnet
Define elastic net regularization object for predictor and external data	define_enet
Define lasso regularization object for predictor and external data	define_lasso
Define regularization object for predictor and external data.	define_penalty
Define ridge regularization object for predictor and external data	define_ridge
Simulated external data	ext_linear
Plot k-fold cross-validation error grid	plot.tune_xrnet
Predict function for "tune_xrnet" object	predict.tune_xrnet
Predict function for "xrnet" object	predict.xrnet
k-fold cross-validation for hierarchical regularized regression	tune_xrnet
Simulated example data for hierarchical regularized linear regression	x_linear
Fit hierarchical regularized regression model	xrnet
Control function for xrnet fitting	xrnet_control
Simulated outcome data	y_linear