Elastic net regression models are controlled by two parameters, lambda, a measure of shrinkage, and alpha, a metric defining the model's location on the spectrum between ridge and lasso regression. glmnet provides tools for selecting lambda via cross validation but no automated methods for selection of alpha. Elastic Net SearcheR automates the simultaneous selection of both lambda and alpha. Developed, in part, with support by NICHD R03 HD094912.
Version: 0.1.0 Depends: R (≥ 3.5.0), glmnet Imports: data.table, ggplot2 Suggests: digest, ggforce, gridExtra, knitr, magrittr, microbenchmark, qwraps2 (≥ 0.4.0), R.rsp, rmarkdown Published: 2019-01-21 DOI: 10.32614/CRAN.package.ensr Author: Peter DeWitt [aut, cre], Tell Bennett [ctb] Maintainer: Peter DeWitt <peter.dewitt at ucdenver.edu> License: GPL-2 URL: https://github.com/dewittpe/ensr NeedsCompilation: no Materials: README CRAN checks: ensr results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=ensr to link to this page.
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