R: Penalized Regression with Hierarchical Nested Parameterization Structure

# Penalized Regression with Hierarchical Nested Parameterization Structure

## Documentation for package ‘hierNest’ version 1.0.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

coef.cv.hierNest | Extract subgroup-specific coefficients from a cv.hierNest object
coef.cv.sparsegl | Extract coefficients from a 'cv.sparsegl' object.
coef.sparsegl | Extract model coefficients from a 'sparsegl' object.
cv.hierNest | Cross-validated hierarchical nested regularization for subgroup models
estimate_risk | Calculate information criteria.
example_data | Example dataset
grouped_one_norm | Calculate common norms
grouped_sp_norm | Calculate common norms
grouped_two_norm | Calculate common norms
grouped_zero_norm | Calculate common norms
gr_one_norm | Calculate common norms
gr_two_norm | Calculate common norms
hierNest | Fit Hierarchical Nested Regularization Model (hierNest)
make_irls_warmup | Create starting values for iterative reweighted least squares
one_norm | Calculate common norms
overlapping_gl | Fit an Overlapping Group Lasso Model
plot.cv.hierNest | Plot method for cv.hierNest objects
plot_contribution | Boxplot or bar chart of per-covariate contributions to the linear predictor
predict.cv.sparsegl | Make predictions from a 'cv.sparsegl' object.
predict.sparsegl | Make predictions from a 'sparsegl' object.
predict_hierNest | Predict Method for hierNest Objects
sp_group_norm | Calculate common norms
two_norm | Calculate common norms
zero_norm | Calculate common norms