eNetXplorer: Quantitative Exploration of Elastic Net Families for Generalized Linear Models

Provides a quantitative toolkit to explore elastic net families and to uncover correlates contributing to prediction under a cross-validation framework. Fits linear, binomial (logistic), multinomial and Cox regression models. Candia J and Tsang JS, BMC Bioinformatics (2019) 20:189 <doi:10.1186/s12859-019-2778-5>.

Version: 1.1.0
Depends: R (≥ 2.10)
Imports: glmnet, stats, graphics, methods, grDevices, Matrix, progress, survival, survcomp, survivalROC, calibrate, RColorBrewer, gplots, expm
Suggests: knitr, rmarkdown
Published: 2019-09-20
Author: Julian Candia and John S. Tsang
Maintainer: Julian Candia <julian.candia at nih.gov>
License: GPL-3
NeedsCompilation: no
Citation: eNetXplorer citation info
Materials: ChangeLog
CRAN checks: eNetXplorer results


Reference manual: eNetXplorer.pdf
Vignettes: eNetXplorer Vignette
Package source: eNetXplorer_1.1.0.tar.gz
Windows binaries: r-devel: eNetXplorer_1.1.0.zip, r-devel-gcc8: eNetXplorer_1.1.0.zip, r-release: eNetXplorer_1.1.0.zip, r-oldrel: eNetXplorer_1.1.0.zip
OS X binaries: r-release: eNetXplorer_1.1.0.tgz, r-oldrel: eNetXplorer_1.1.0.tgz
Old sources: eNetXplorer archive


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