R: A Fast Algorithm for Kernel Quantile Regression

# A Fast Algorithm for Kernel Quantile Regression

## Documentation for package ‘fastkqr’ version 1.0.1

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

## Help Pages

coef.cv.fastlqr | Extract Coefficients from a cv.fastlqr Object
coef.fastlqr | Extract Coefficients from a fastlqr Object
coef.kqr | Extract model coefficients from a 'kqr' object.
coef.nckqr | Extract model coefficients from a 'nckqr' object.
cv.kqr | cross-validation for selecting the tuning parameter of kernel quantile regression
cv.nckqr | cross-validation for selecting the tuning parameter 'lambda2' of non-crossing kernel quantile regression
cv.qr | Cross-Validation for Regularized Linear Quantile Regression
kqr | Solve the kernel quantile regression. The solution path is computed at a grid of values of tuning parameter 'lambda'.
nckqr | Solve the non-crossing kernel quantile regression
predict.cv.fastlqr | Predict from a cv.fastlqr Object
predict.fastlqr | Predict from a fastlqr Object
predict.kqr | Predict the fitted values for a 'kqr' object.
predict.nckqr | Predict the fitted values for a 'nckqr' object.
qr | Regularized Linear Quantile Regression