PenalReg - Automated Penalized Regression Analysis Using Ridge, Lasso and
Elastic Net
Provides an automated framework for penalized regression
analysis using Ridge Regression, Lasso Regression and Elastic
Net Regression. The package performs data standardization,
training-testing data partitioning, cross-validation for
hyperparameter tuning, model fitting, coefficient estimation,
variable importance assessment, prediction, and performance
evaluation. It simplifies regularized regression analysis by
integrating the complete modeling workflow into a single
function suitable for researchers for better understanding of
the data.The methods are based on Hoerl and Kennard (1970)
<doi:10.1080/00401706.1970.10488634>, Zou and Hastie (2005)
<doi:10.1111/j.1467-9868.2005.00503.x>, and Friedman et al.
(2010) <doi:10.18637/jss.v033.i01>.
