R: Regularization Paths for Regression Models with Grouped Covariates

# Regularization Paths for Regression Models with Grouped Covariates

## Documentation for package ‘grpreg’ version 3.6.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

AUC | Calculates AUC for cv.grpsurv objects
AUC.cv.grpsurv | Calculates AUC for cv.grpsurv objects
Birthwt | Risk Factors Associated with Low Infant Birth Weight
birthwt.grpreg | Risk Factors Associated with Low Infant Birth Weight
coef.cv.grpreg | Model predictions based on a fitted 'grpreg' object
coef.grpreg | Model predictions based on a fitted 'grpreg' object
cv.grpreg | Cross-validation for grpreg/grpsurv
cv.grpsurv | Cross-validation for grpreg/grpsurv
expand_spline | Expand feature matrix using basis splines
gBridge | Fit a group bridge regression path
gen_nonlinear_data | Generate nonlinear example data
grpreg | Fit a group penalized regression path
grpsurv | Fit an group penalized survival model
logLik | logLik method for grpreg
logLik.grpreg | logLik method for grpreg
logLik.grpsurv | logLik method for grpreg
Lung | VA lung cancer data set
mfdr | Marginal false discovery rates
plot.cv.grpreg | Plots the cross-validation curve from a 'cv.grpreg' object
plot.grpreg | Plot coefficients from a "grpreg" object
plot.grpsurv.func | Plot survival curve for grpsurv model
plot_spline | Plot spline curve for a fitted additive model
predict.cv.grpreg | Model predictions based on a fitted 'grpreg' object
predict.grpreg | Model predictions based on a fitted 'grpreg' object
predict.grpsurv | Model predictions for grpsurv objects
print.summary.cv.grpreg | Summarizing inferences based on cross-validation
residuals.grpreg | Extract residuals from a grpreg or grpsurv fit
select | Select an value of lambda along a grpreg path
select.grpreg | Select an value of lambda along a grpreg path
summary.cv.grpreg | Summarizing inferences based on cross-validation