R: Fast Algorithm for Penalized Quantile Regression

# Fast Algorithm for Penalized Quantile Regression

## Documentation for package ‘hdqr’ version 1.0.2

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

## Help Pages

coef.cv.hdqr | Extract Coefficients from a 'cv.hdqr' Object
coef.cv.nc.hdqr | Extract Coefficients from a 'cv.nc.hdqr' Object
coef.hdqr | Extract Model Coefficients from a 'hdqr' Object
coef.nc.hdqr | Extract Model Coefficients from a 'nc.hdqr' Object
cv.hdqr | Cross-validation for Selecting the Tuning Parameter in Penalized Quantile Regression
cv.nc.hdqr | Cross-validation for Selecting the Tuning Parameter of Nonconvex Penalized Quantile Regression
hdqr | Fit the high-dimensional linear quantile regression with elasticnet regularization. The solution path is computed at a grid of values of tuning parameter 'lambda'.
nc.hdqr | Solve the Penalized Quantile Regression with Nonconvex Penalties
predict.cv.hdqr | Make Predictions from a 'cv.hdqr' Object
predict.cv.nc.hdqr | Make Predictions from a 'cv.nc.hdqr' Object
predict.hdqr | Make Predictions from a 'hdqr' Object
predict.nc.hdqr | Make Predictions from a 'nc.hdqr' Object