Hierarchical Regularized Regression
Get coefficient estimates from "tune_xrnet" model object.
Get coefficient estimates from "xrnet" model object.
Define elastic net regularization object for predictor and external da...
Define lasso regularization object for predictor and external data
Define regularization object for predictor and external data.
Fit hierarchical regularized regression model
Simulated outcome data
Define ridge regularization object for predictor and external data
Simulated external data
Plot k-fold cross-validation error grid
Predict function for "tune_xrnet" object
Predict function for "xrnet" object
k-fold cross-validation for hierarchical regularized regression
Simulated example data for hierarchical regularized linear regression
Control function for xrnet fitting
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.
Useful links